Answering "is the workspace where the agent runs, or what it works
on?" — it is what it works on, and conflating the two is dangerous
rather than merely untidy.
The agent commits its workspace with git add -A and pushes it, so
anything inside the clone reaches the project repository. A .env
placed there would publish the LiteLLM, Matrix and Gitea tokens as a
side effect of the agent working correctly: silently, once, and
probably unnoticed. Startup now refuses both that and a state store
inside the clone, and .env.example documents the intended layout.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Nothing had ever assembled the agent. main.py was still the hello-world
placeholder from the scaffold, and no code outside the test suite
constructed an Orchestrator — which is how two fully built, fully
tested components came to be reachable from nothing: the delegation
harness, and the Gitea comment poller. Unit tests that construct a
component directly cannot catch that; only assembly can.
- config.py validates every variable before anything is built and
names all of them at once, rather than failing at first use twenty
minutes into a milestone on the call that mattered. Whitespace-only
counts as missing, since a token of spaces passes a truthiness check
and fails at the first request instead
- agent.py builds the whole graph and owns startup and shutdown order:
reconcile before accepting commands, and on stop, stop watching,
then stop talking, then close the store last
- The Gitea account is read via whoami rather than configured: it names
the identity every permission is evaluated against, and proves the
token works before anything depends on it
- Poller lifecycle is now a state-machine concern: watch the plan issue
while a gate stands, the PR while it is open, and stop on leaving.
The orchestrator owns when to watch; an injected factory owns how to
build one
- The executor reports each turn, because it runs synchronously inside
the transport callback: without it the agent is silent for a whole
milestone and a working run looks exactly like a hung one
- main.py loads .env, builds, and shuts down cleanly on SIGINT/SIGTERM
The entry-point tests changed shape: nisse-dev no longer greets, it
refuses to start unconfigured and says everything that is missing. Both
tests now run with a deliberately empty environment and a .env path
that does not exist, because the working directory's .env holds live
credentials and a test must never be one cwd away from starting a real
agent.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Two gaps found by auditing spec against code, the second created by
7b landing the harness without its boot-time half.
**The harness was not connected to anything.** Only a live test
constructed a Delegation; A12's failure-count trigger still gated to
the human, which A13 describes as the fallback rather than the path.
Consecutive command failures now hand the sub-task to the delegate,
with the failures in the brief so it need not rediscover what the
local model learned the hard way. A usable handback lets the local
loop carry on; anything else escalates, because a cap breach leaves a
half-edited tree.
**A3 step 5 was unimplemented.** A crash mid-delegation failed safe —
boot gated on "restarted mid-EXECUTING" — but always gated, even on
the clean cut the spec says should resume, and left the branch orphaned
because _abandon only runs while the process lives.
- A delegation now records an intent before the branch exists, and
settles it whichever way the delegation ends; an aborted delegation
is a finished one, and leaving it pending would make the next boot
believe work was still in flight
- delegation_verdict implements the clean-cut test as an observable
check, never model self-assessment: settled if a completion follows
the start, absent if the branch was never created, gate on a
tool_call with no recorded result, resume otherwise
- recover() sweeps at boot, announcing a resume with a notice rather
than a question, since a clean cut needs no decision from the
operator, and leaving an unclean one pending so the generic sweep
gates on it
- resume() continues the same delegation rather than starting a
second: no new branch, no second delegation_started, because A10
defines a session as the delegation, not the process lifetime
Honest limit, stated in the code: "the branch sits at the expected
commit" is approximated by the branch existing and carrying the work,
since per-turn shas are not recorded in the log, so a branch rewritten
underneath us would go undetected.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Completes step 7.
- expert.py: one stateless call for a question needing no repo access.
Structured output is contracted at the prompt level, since vendors
differ on JSON enforcement, so the reply is parsed and validated
locally with one retry — tolerating a fenced code block, because
models wrap JSON habitually, but not missing fields
- The per-task budget is counted from the canonical log rather than
memory, so it survives a restart and cannot hand a circling executor
a fresh allowance. Exhaustion raises rather than answering: a caller
out of consults should get on with the work or escalate
- Consults are recorded as delegation_started/completed with role
consultant. A16 asks for a "consult/delegation eval set", and
reusing the composite events gets consult evaluation for free rather
than inventing a parallel record
- evals.py pairs starts with completions into eval records, with
verdicts kept outside the canonical log: the log records what
happened, a verdict is a later judgement about it, and judgements
get revised. Schema v3 adds the outcomes table, so a v1 store now
traverses two migrations — a better exercise of the hook than one
- ask_expert is offered to the executor as a tool only when a desk is
configured, in addition to the observable escalation triggers and
never instead of them (A12). Consulting is not mutating, so a
completion claim backed only by consults is still challenged
Found live: passing an empty message list and putting the question in
the system prompt fails outright — the Messages API requires at least
one non-system message. The question now travels as a synthesised user
message that is never appended to the log, which keeps the consult
stateless while remaining a valid request.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Observed rather than assumed, after checking the running instance:
collections carry per-user permissions in three tiers and permissions
are collection-scoped, not per-document. So one collection per writing
principal, with read membership for everyone else.
- States precisely what that enforces: no other agent can write a
given agent's world model. It does not enforce operator-versus-agent
exclusion, since the operator holds manager on their own wiki; that
half is procedural, via the break-glass routine that stops the
agents first. Two different strengths, so the spec no longer implies
one guarantee covers both
- Per-user grants, not groups: Outline groups are not federated with
LLDAP, so using them would put membership somewhere nothing syncs.
Three principals make the manual mapping trivial
- Outline API keys are per-user, so each agent's token must belong to
that agent's own Outline user. A token minted from an admin account
voids every boundary above while appearing to work — the same shape
as the Gitea permission surprise
- Collections identified by ID from config, documents by ID recorded
in the state store, which also makes writes idempotent across a
retry
- The conditional-write requirement softens to a revision *read*:
break-glass stops the agents, so compare-and-swap is unnecessary and
only divergence detection is needed for A3
Also records Outline's MCP server as considered and deferred. A17's
enforcement depends on this library sitting between the model and the
store; MCP's purpose is direct model access, and a procedure the model
may decline to fetch does not constrain it. Still a candidate for the
discretionary search tool, with two things to verify first.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Two loose ends in the A17 amendment, both found by asking whether the
build order needed changing:
- A17 requires retrieved content to be snapshotted into the canonical
log, but A10's event table — the authoritative list — had no row for
it, so an implementer reading A10 would never know to add one.
knowledge_retrieved now carries the text as read, the document ID,
its revision, and when it was read
- Part G step 10 already scheduled Outline, so the ordering does not
change; it now names A17 rather than only Part D, and says which
half arrives first — the world model, with operator procedures
waiting on the C2 taxonomy they bind to
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Part D said what Outline is for but never how to build against it —
the only external integration with no A-series component, while
Transport, LLM, Browser, Secrets, SSO and Logging all have one. A17
supplies the contract.
Settled here:
- Sharing is read access, never write access. Every document has
exactly one writer, so concurrent writers never exist and Part D's
last-write-wins objection disposes of itself. Default shared
membership is operator + nisse-ops; nisse-dev gets private space
only, since B3 seals it from the LAN and a shared network map is a
map of what it is sealed from
- Agent-owned knowledge is always a cache, never authority: rely on
it to know what exists and where to look, verify a specific fact
against the live system before acting on it
- Enforcement is structural, because a prompt is not enforcement. A
model cannot be stopped from believing what it reads, so the
enforceable goal is narrower — an unverified belief must not become
an irreversible action — and four mechanisms carry it, leaning
hardest on surfacing provenance at the human gate that C2 already
requires
- Never an instruction channel and never an approval channel, stated
both here and in A4 where approvals are specified
- Corrections flow through transport rather than direct edits, which
is better provenance: a hand edit is invisible to the agent's
record, an instruction is authenticated, logged, and reconcilable.
Break-glass reuses Part F's idle flag
- Retrieved content is snapshotted into the canonical log, since A10
forbids a mutable provider handle being the only reference — with
the A3 consequence that boot must re-fetch snapshots for resumed
tasks
- Outage posture is asymmetric: write failures never block, but a
failed read of a procedure bound to a confirm-first action gates,
because proceeding is acting unconstrained on exactly the operation
someone wrote a procedure for
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
CI failed on the delegation branch with a 429 from the proxy: token
limit 200000, 17399 remaining. Not a defect — the live delegation
tests are token-hungry, and every push to a PR branch fired two
identical suites concurrently, since the push and pull_request events
both matched.
- Push now only triggers on main. A PR branch is already covered by
the pull_request event, so this halves both the wall time and the
tokens spent per branch
- A 429 is retried once before being surfaced. Losing a ten-turn
delegation to a transient limit wastes far more than waiting out
the window, and retrying forever would hide a real ceiling. The
sleep is injectable, so the existing 429 test no longer waits 20
seconds for real
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
A frontier model receives a scoped sub-task, works autonomously with
full tool access, and hands back; the local loop reads the handback
note and the file state, never the reasoning.
- Branch at delegation start, and abort discards it. That required
committing each turn's work onto the branch: without commits,
deleting a branch discards nothing, so "abort discards the work"
was a comforting phrase rather than a fact. The caller's own
in-flight changes are committed to their branch first, so an abort
cannot destroy work nobody delegated
- Hard caps on turns and wall clock; a breach is a defined failure
return, and its result is not usable, so the caller gates rather
than resuming on a half-edited tree
- Every event is checkpointed as it arrives, so a crash mid-delegation
leaves the branch at a known commit and a truthful transcript
- Handback is validated locally: blank fields or a non-boolean success
flag are refused and the delegation continues rather than accepting
a useless note
Two failure modes found by running it against a real model:
- A success claim with nothing changed was accepted. The handback plus
file state is the entire interface back, so a note describing work
that does not exist is worse than no note. Success now requires a
successful mutating tool call; reporting failure still does not,
since "this is impossible" is a legitimate finding
- The delegate invented the absolute path /workspace, wrote there, ran
its tests there, and handed back truthfully — with the repo empty
and git seeing nothing. Writes outside the workspace are now refused
with a message naming the real root, and both prompts state where
the workspace is instead of leaving the model to guess. This is not
sandboxing: work outside the repo is invisible to git, so the
milestone would publish an empty PR
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The second renderer adapter, and the concrete case for A13's decision
to normalise in the renderer rather than on the wire. The two vendors
disagree structurally, not cosmetically: the system prompt is a
top-level field rather than a message, a tool call is a tool_use
content block rather than an array, a tool result is a block inside a
user message rather than a "tool" role, and tool schemas use
input_schema rather than parameters. A middlebox flattening those
would be lossy exactly where a long-running delegation lives.
- render_anthropic.py builds vendor-native /v1/messages bodies from
the canonical log, coalescing adjacent same-role blocks so a
tool_result lands directly after its tool_use
- Tool manifests are declared once in OpenAI shape and converted per
vendor, so adding a tool does not mean editing two places
- AnthropicPassthroughClient implements the same LLMClient protocol,
so callers pick a route rather than a different kind of client, and
maps provider tool ids to canonical ones at the boundary
- Dangling tool calls get a placeholder result here too; this API
rejects them more strictly than the OpenAI shape
- Vendor-opaque reasoning blocks are dropped for now with the reason
recorded: A10 wants them stored and never replayed across sessions,
and the canonical schema has no event for that yet
Live tests prove the body is accepted as sent, that a tool_result
turn round-trips, and — as A5 asks — that prompt cache accounting
survives the passthrough rather than being flattened by the proxy.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The previous fix challenged a completion claim made before any tool
call, but treated every tool as work — so a model that ran one
list_dir and then declared the milestone done was believed, and CI
caught the same empty milestone again.
Reading a file or listing a directory is the model orienting itself.
Only write_file and run_command now count, so a completion claim must
be backed by something that changed or verified the tree.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
B2 specified the service account and its scoped token but never said
the project repo's default branch must be protected — which turns out
to be the load-bearing part of the PR gate.
In Gitea, write access includes merging pull requests, and repository
ownership does not restrict merging either. So an agent with the
access it needs to push branches can also merge its own PR, and the
review gate holds only because the agent's code does not call the
merge endpoint. That is the advisory guarantee A4 exists to rule out.
Verified rather than assumed: before protection was configured, the
agent's own token merged its own PR (HTTP 200). With protection it is
refused (405), as is a direct push to the default branch. The
amendment says to assert both, so relaxing the protection later fails
a test instead of silently removing the gate.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
CI caught the executor recording an empty milestone as a success: the
model answered with prose on its first turn, and the loop reads "no
tool call" as "the plan is done". It had therefore finished a
milestone having touched nothing, and the milestone would have gone
on to publish with no changes.
A completion claim is now challenged once when no tool has been
called yet — the same shape as the planner's nudge — and a model that
persists escalates instead of reporting success. After the first tool
call the claim is taken at face value, as before.
The live milestone test failed roughly one run in five on this; four
consecutive runs pass now.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
- approvals.py: PlanBoard opens one issue per project and posts each
plan revision as a comment carrying its rev tag. The state store
keeps only a pointer, so gate state can be re-derived from Gitea
after a state-volume loss — external truth wins
- Gitea comments are a second approval source: revision binding, the
typed word approve, and first-approval-wins work exactly as over
transport, with a per-channel allowlist because a Gitea login is
not a Matrix MXID
- Outcomes are echoed to the other channel, so the two records cannot
silently disagree about what was approved
- A Gitea outage degrades durability of the record, not the ability
to approve: planning proceeds and Matrix remains a complete channel
- Live test now asserts the server refuses the agent's own merge and
its push to the protected branch. That property was previously
true only because our code did not attempt it; branch protection
makes it structural, and this test fails if the protection is ever
relaxed
- Fixed a race in the process-group test: killing a group is
asynchronous and the grandchild is an orphan, so its exit is not
synchronised with our return; the test now waits for death
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
- poller.py: CommentPoller polls PR comments rather than taking
webhooks, keeping the VM outbound-only (B3). On an outage it backs
off exponentially, caps, and retries indefinitely while logging:
polling is pure intake, so an outage delays a reaction but never
fails a task or forces a transition
- prime() marks the existing thread as seen without delivering it, so
starting a watch does not re-address feedback already handled
- Review loop: a comment in PR_OPEN enters the canonical transcript,
the executor responds, and the fix is pushed to the same branch with
a reply on the PR. No intent is recorded for a follow-up push — the
PR already exists, so a repeated push is harmless, unlike opening a
second PR
- Comment authors are checked against a separate Gitea operator
allowlist: a PR comment is an instruction channel into an agent that
writes code, so it is operator-scoped, and a Gitea login is not a
Matrix MXID (A4 per-channel allowlists)
- Orchestrator now holds a lock: transport and the poller deliver on
separate threads, and state transitions must not interleave
- Backoff timings are injectable, so the outage path is tested in
milliseconds instead of being untestable
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Completes the B1 loop past EXECUTING, and answers the question raised
reviewing #6: PR acceptance is a milestone's final gate, so there is
no separate FINISHED state — completion returns to milestone planning
or to IDLE.
- publish.py: MilestonePublisher commits the work on a task-namespaced
branch, pushes, and opens a PR carrying the approved plan. Intent is
recorded before the first externally visible act, so a crash
anywhere in the sequence leaves a durable record and boot
reconciliation asks Gitea whether the PR exists rather than opening
a second one
- Nothing to commit is reported, not raised: the executor may
legitimately conclude there was nothing to change
- control.py: PR_OPEN state with EXECUTING -> PR_OPEN and
PR_OPEN -> {MILESTONE_PLANNING, IDLE}; operator commands
'next milestone' and 'project complete'
- A configured publisher always contributes its own reconciler at
boot, so an interrupted publish is settled against external truth
without the caller having to remember to register it
- A publish failure gates to the operator rather than retrying into a
possible duplicate
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Operator does not want nightly or weekly runs. Pushes to main already
cover code changes, so the remaining addition is workflow_dispatch: a
manual re-run for after a credential rotation or a budget top-up,
which also retires the empty-commit trick used to pick up new secrets.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Pushes to main already trigger a full run, so code changes were
covered. What was not: the live tests depend on external state that
drifts with no commit at all — the LiteLLM budget filling up, a model
withdrawn from the proxy, a token revoked or expired. A nightly run
against the default branch surfaces that the morning it happens
instead of mid-task.
workflow_dispatch adds a manual trigger, which also removes the need
for the empty-commit trick used earlier to pick up new secrets.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
find_pull_request read only the newest 50 per state, so once a repo
passed that many pull requests a "not found" would mean "not in the
newest page" — and the A3 reconciler would read that as "the PR was
never opened" and open a duplicate. Exactly the side effect the
intent log exists to prevent.
It now pages until a short page proves the end, and raises rather
than answering "absent" from an incomplete search; the reconciler
turns that into unverifiable and gates to the human.
Found while wiring CI: every CI run opens a PR in the sandbox, so the
threshold would have been crossed in weeks rather than never.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The standalone half of the Gitea layer; orchestrator wiring follows
once the executor loop lands, to avoid colliding with it in
control.py.
- gitea.py: GiteaClient over httpx — open PRs, list and post issue
comments, close PRs. find_pull_request is the A3 external-truth
query that makes opening a PR idempotent across a crash, and it
checks closed PRs too, since a crash after opening must not be
answered with "nothing is open, so open another"
- pull_request_reconciler: an unreachable Gitea returns None rather
than a guess, so the agent gates to the human instead of risking a
duplicate side effect
- git.py: branch, commit, push for the workspace. The token is passed
per-invocation rather than stored as a remote, so it never lands in
.git/config, and anything raised is scrubbed of it
- commit_all returns None when there is nothing to commit: an empty
milestone is a fact to report, not an error
- Live test does the real round trip against the sandbox repo and
cleans up after itself
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Two invariants only a live homeserver can check, now enforced rather
than verified by hand:
- The configured NISSE_MATRIX_USER_ID must be the token's real owner.
MatrixTransport filters its own messages by comparing sender to that
value, so a mismatch would make the bot read its own posts as
operator input.
- The account must be a testing identity, so a stray live run can
never act as the production agent.
Both hold today; this keeps them holding when the production
nisse-dev account is created.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Found while chasing a flaky live test, but the flakiness was a real
bug: only the ask_human path recorded a pending item, so AWAIT_INPUT
reached any other way — planning failure, stopped milestone, boot
reconciliation — refused every operator reply with "no pending
question to answer" and the agent could never be recovered. The
operator had no way back short of wiping state.
Every path into AWAIT_INPUT now records what a reply should resume,
and answering dispatches on it: planning failures and questions
resume planning, a stopped milestone returns to its still-approved
gate, and the fallback says what commands work instead of
dead-ending. Two regression tests cover the recovery paths.
The live test also scripted a fixed approve/approve/start sequence,
which a real model breaks by legitimately calling ask_human at a
gate. It now plays the operator adaptively, responding to whatever
the agent actually did. Five consecutive live runs pass.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
os.kill(pid, 0) succeeds on a zombie, and a killed orphan stays a
zombie until reaped — which never happens inside a CI container with
no init. The test read that as "still alive" and failed there while
passing locally. It now reads the process state from /proc, with a
control assertion so a broken liveness check cannot pass silently.
The group kill itself was correct.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
- tools.py: four flat tools (read_file, write_file, list_dir,
run_command) per A15's reduced manifest. Deliberately unsandboxed:
the VM is the trust boundary (B3) and tool use is auto-approved
inside an approved unit of work (A4), so path confinement would add
failure modes without adding safety. What is enforced is
operational — timeout with process-group kill so a backgrounded
server cannot outlive its command, output truncation so a build log
cannot eat the context window, closed stdin so prompts fail fast,
and a scrubbed environment so project code never sees the agent's
credentials
- executor.py: renders the log, calls the executor role with the
reduced manifest, dispatches tool calls, and checkpoints every
result (A13). Escalation is observable, never self-assessed (A12):
consecutive command failures and a hard turn cap. Failed reads do
not count — looking around is not failing
- Until delegation exists (step 7), escalation gates to the human
with the failures attached
- control.py: start milestone now runs the executor; a stopped
milestone gates to AWAIT_INPUT
Two bugs found by running it live against real models:
- A turn-ending gate tool (submit_plan) left a tool_call with no
tool_result, which providers reject outright, so every planning
turn after the first failed with a 400. The planner now records the
gate as the call's outcome, which is also the truthful transcript
- The renderer now emits a placeholder for any tool_call lacking a
result, so a crash between call and result (A3) cannot poison the
transcript permanently
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Empty commit: Gitea 1.27 exposes no rerun API endpoint, and Actions
secrets are read at run start, so a new run is needed to exercise the
live planning test.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The virtual key now reaches a Haiku-class route, which holds the
tool-call contract llama3.2 could not: a real planning turn returns a
well-formed submit_plan call with an explicit, low-inference plan.
Wires NISSE_LIVE_PLANNER_MODEL through the CI workflow (add the
matching Actions secret to run it there) and records the finding in
.env.example.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
- planner.py: LLMPlanningAgent offers exactly two tools, submit_plan
and ask_human, so gating stays structural at the tool layer; no
proceed tool exists. System prompt requires explicit, low-inference
plans because a weaker model executes them (A13)
- Model output is appended to the canonical log as it arrives, before
being interpreted, so a crash mid-planning leaves a truthful
transcript
- A bad turn (prose instead of a tool call, malformed arguments, or a
failed call) retries once, then raises PlanningError; the
orchestrator gates to AWAIT_INPUT rather than inventing a plan
- Orchestrator: appends every operator message, plan_submitted, and
gate_opened to the transcript, so re-planning sees rejection
feedback as conversation rather than out-of-band parameters; pins
the A11 role mapping at task start
- llm.py: non-JSON or non-object tool arguments now raise LLMError
instead of escaping as JSONDecodeError — observed from llama3.2,
which emits truncated argument strings
- Live planning test is opt-in on NISSE_LIVE_PLANNER_MODEL: planning
escalates unconditionally (A12) and the local model does not hold
the tool-call contract, so it awaits a frontier route
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Skipping now keys solely on NISSE_LLM_BASE_URL and
NISSE_MATRIX_HOMESERVER: if the sentinel is set, the live path is
expected to work and any other missing variable is an assertion
failure naming it, not a silent skip. A misnamed or misplaced CI
secret previously produced a green run with no live coverage.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The integration step now receives the LLM and Matrix env vars from
repo secrets, so the live smoke tests run in CI when the runner can
reach the services; the skip-guards keep a missing secret or
unreachable service as a skip, never a failure. -rs surfaces skip
reasons in the CI log for diagnosis.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- matrix.py: Transport implementation over the Matrix client-server
HTTP API directly (token auth, /sync long-poll, /send) using the
existing httpx dependency — no Matrix SDK; four endpoints total.
Deviation from the presented plan (matrix-nio) flagged in the PR
- First sync learns position and skips backlog, so room history is
never delivered as context (A1); own messages and non-message
events filtered; sender MXID passed through for the orchestrator's
operator allowlist
- Sync loop backs off (capped at 60s) and retries indefinitely on
homeserver errors, mirroring B2's polling posture
- Encrypted rooms unsupported: bot rooms are created unencrypted
until E2E lands (operator decision; room recreated accordingly)
- NISSE_MATRIX_TEST_ROOM_ID added: the live smoke test binds only
to the dedicated test room, never the production room
- 8 unit tests over a mocked HTTP layer; live integration test
verified against the real homeserver
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
PR 2 of the steps-3/4 plan.
- llm.py: LLMClient protocol — complete(events, tools, model) ->
canonical events — present from the first real LLM call.
LiteLLMClient renders requests via the A10 renderer, targets the
proxy's OpenAI-compatible route, and maps provider tool-call IDs
to locally-minted canonical IDs at the boundary
- RoleMap (A11): executor/planner/delegate/consultant resolved from
env; pinned() returns the mapping to record at task start
- Config strictly from env: NISSE_LLM_BASE_URL, NISSE_LLM_TOKEN;
envfile.py is a minimal .env loader where real env wins; .env now
gitignored with a committed .env.example documenting all variables
(Matrix ones included for the upcoming transport PR)
- Live smoke test against the proxy is integration-marked and skips
without credentials — CI stays credential-free per operator
decision; the test runs locally once .env exists
- httpx added as nisse-dev's HTTP client
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
dongar
dev-agent