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Author SHA1 Message Date
pragent-bot 78bcf6a9a0 feat(review): multi-lens orchestration — 5 parallel opencode subprocesses (security/docs/code-quality/tests/perf) 
On by default, opt-out via "reviewers": []. 290 tests pass.

- pilot/opencode_review.py: ReviewerSpec dataclass, default_reviewers(),
  parse_reviewers_config(), parse_triage_config(), resolve_reviewers(),
  _normalize_lens_finding(), posthash() (matches feedback.py scheme),
  _agreement_hash() (severity-free for cross-lens promotion), _tone_strip(),
  synthesize() 7-stage (severity_floor → tone-strip → length cap → per-lens
  max → per-file cap → dedup by _posthash → cross-lens severity promote →
  per-PR cap), run_lenses() (ThreadPoolExecutor pool=4), triage(),
  _intersect_with_triage(), _filter_by_skip_if(), run_lenses_review().
  run() routes to fan-out when config.reviewers[] present or PRAGENT_REVIEWERS=1.
- pilot/ai_review.py: parse_repo_config learns reviewers[] and triage objects
  (id regex /^[a-z0-9][a-z0-9-]{0,31}$/, 8-entry cap, agent_file/model/
  severity_floor/max_findings/activation/skip_if_all_changed_paths/hotpath_globs).
  review_pr branches to opencode_review.run_lenses_review when configured.
  _render_collapsible_usage shows lenses: ... line when present.
- .opencode/agents/{docs,code-quality,triage}.md: 3 new lens subagents.
- .opencode/skills/lens-orchestration/SKILL.md: strict-JSON contract every
  lens subagent MUST honor.
- .opencode/agents/pragent.md: slim to coordinator; no more hardcoded
  @security/@tests/@perf delegation; loads lens-orchestration skill.
- .opencode/README.md: rewrite 'Add a review lens' recipe for multi-lens.
- pilot/README-webhook.md: new 'Multi-lens pipeline' section (diagram +
  default roster + config schema + env vars + cross-lens dedup contract).
- tests: 36 new tests (test_ai_review.py +12 reviewers/triage/usage,
  test_opencode_review.py +24 orchestration). posthash golden-vector matches
  feedback.py exactly across 5 severity × 2 line cases.
 2026-08-20 22:16:21 +00:00
Marcos 998f793ec2 feat(agent): tighten prompt to bound beyond-diff reads + de-generalize cost-model labels 
Three changes from operator feedback:

1. Per-comment � attribution restored on inline comments (operator wants
   it back — the PR-level collapsible is collapsed by default, so the
   attribution is the visible signal of per-finding cost share).
   Hidden only when no _tok_attrib was computed (legacy callers / ollama
   path without usage metering).

2. Agent prompt now bounds reads beyond the diff — the single biggest
   driver of input-token bloat on long agent loops:
     * ≤ 5 file reads beyond the diff for the entire review
     * ≤ 80 lines per read (use --offset + --limit)
     * ≤ 3 grep calls beyond the diff (prefer rtk grep)
     * no re-reads of files already seen
     * no directory walks (ls -R, find .)
     * honor .pr-review.json:exclude_paths

3. De-generalize cost_model calibration labels. The OBSERVED_RUNS list
   referred to `gitea_admin/pragent#7` — a real internal repo path that
   blocks commercialization. Replaced with `internal/hardening-PR (16
   files, 1020 insertions / 91 deletions)`. The numbers (input/output
   tokens, steps, duration) are unchanged — only the labels are
   generic.

Tests:
  * test_inline_comment_body_with_attribution_line — asserts 🪙 line
    shows when _tok_attrib is set
  * test_inline_comment_body_no_attribution_no_coin_line — still
    verifies the line is hidden when no attribution data
  * test_observed_report_prices_every_model — asserts no internal
    repo name appears in the rendered report
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-08-20 17:35:06 +00:00
Marcos f6be2b3c61 feat(review): PR-level collapsible metadata + emoji-tagged inline comments 
PR-level comment layout (per operator's format guide):
  * Summary of Changes — 2-4 bullets, sourced from the agent's new
    `summary_changes` JSON field. Falls back to splitting the prose
    `summary` if the list is missing.
  * Key Risks & Concerns — bullets from the new `risks` JSON field.
  * Findings Overview — Markdown table covering every finding
    (severity emoji / location / one-line problem). Both anchored and
    unanchored findings appear here so the table is the single scan point.
  * Unanchored Notes — bullets with severity + fix + Markdown-linked ref,
    for findings with no post-change line to anchor.
  * AI Usage & Run Details — wrapped in a <details>/<summary> collapsible
    so the body stays scannable. Cost line stays inside it.

Inline comment shape:
  * Severity badge: 🔴 [HIGH] / 🟡 [MEDIUM] / 🔵 [LOW] / ⚪ [INFO].
    Unknown severities fall back to � [INFO].
  * 1-2 short paragraphs of problem; **Fix:** label for the fix line.
  * Standard ```suggestion fence for replacement code (Gitea/Forgejo
    apply-on-click). Language-tagged fences are no longer used for
    single-file diffs.
  * Reference as a Markdown hyperlink, visible label truncated to
    <=60 chars; the underlying URL is preserved verbatim.
  * NO per-comment 🪙 token attribution. All telemetry stays in the
    collapsible block on the PR-level comment.

Agent prompt updated to emit `summary_changes` and `risks` in the JSON
output (backward-compatible — older outputs missing them still parse;
they fall back to splitting the prose `summary`).

Tests: 15 new (severity emoji mapping, reference truncation, findings
table escaping, collapsible usage rendering, summary_changes+risks
layout). Existing tests updated for the new structure.
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-08-20 16:51:20 +00:00
Marcos 5302e8dcd7 fix(review): salvage findings from nested-object fences + bare arrays + unfenced tail JSON 
The canalhandia PR review lost all findings because the agent ran out of
context before emitting the closing json fence. Three failure modes hit
the old regex \{.*?\}:
  * nested objects inside the fence truncated at the first }
  * bare arrays (no {summary, findings} wrapper) returned []
  * unfenced JSON in the prose tail was never reached (first not last)

Replace the regex with a balanced-brace scanner:
  * _last_json_block walks the fence contents with a depth counter so
    nested objects survive
  * _last_balanced_json + _balanced_json_substring handle bare arrays and
    prose-tail JSON when no fence is present
  * _parse_json_tolerant returns list as well as dict; parse_findings and
    parse_review_output accept a bare array as the outer value

Agent prompt tightened: reserve the final step for emitting the JSON
block so the analysis isn't lost when context runs out.

10 new tests in tests/pilot/test_ai_review.py cover the new shapes.
Co-Authored-By: Claude <noreply@anthropic.com>
 2026-08-20 16:29:44 +00:00
Marcos f59b906395 chore: scrub private infrastructure for a public repo, rewrite README 
Audited the working tree and all 26 commits of history for credentials: none
found. No API keys, no private keys, no tokens — the live bot token, webhook
secret and admin token appear nowhere in the repo or its history.

What was there was infrastructure disclosure, which is recon material rather
than a leak, but has no business in a public repo:

- Tailnet addresses and cluster-internal hostnames in code, docs and the CI
  template. The model endpoint is now supplied at runtime via
  PRAGENT_MODEL_BASE_URL and patched into opencode.json by install_config();
  the committed config carries a placeholder, guarded by a test.
- A host path (/home/marcos) as the default rtk directory — now unset.
- Real usernames in the onboarding docs — now alice/acme.
- A standing list of one-time setup tokens that were never revoked, named
  individually. Removed. Note that removing the list does not revoke the
  tokens: they should still be revoked in the Gitea admin UI.

The substitution happens in Python rather than via opencode's {env:VAR} config
templating, because the reviewer subprocess runs with an allow-listed
environment — resolving it before the process starts keeps that allow-list from
having to grow.

README rewritten for a reader who has never seen the project: what it does and
what that output looks like, honest status (pilot works, framework designed but
unbuilt), the security model up front given what this thing is, and the measured
cost numbers including the two effects that make naive estimates wrong.

History still contains the old addresses. They are tailnet-only and not
credentials, so no rewrite.

Tests: 131 -> 137.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01B11e8TZZxJyzHW7jj7KWUN
 2026-08-18 12:59:52 +00:00
Marcos 30d2a3d7da feat(factory): five review skills + a per-review cost model 
Skills — the primary now loads conditionally (each one is input tokens), per a
load table in pragent.md:

- attention-tiering: classify every PR trivial/lite/full/oversized BEFORE
  reading anything, and cap file reads, linter runs and subagent fan-out per
  tier. This is the cost governor; the other skills defer to its budget.
- linter-playbook: per-ecosystem detect-and-run commands scoped to changed
  files, the never-install rule, and how to turn a diagnostic into a finding
  instead of pasting tool output.
- security-lens: the inline security checklist for when @security isn't worth
  delegating, built around a source -> sink test each finding must pass.
- malicious-change: hostile-PR detection — injection aimed at the reviewer,
  install/CI-time hooks, obfuscated payloads, dependency confusion, logic
  backdoors. Complements the runtime containment added in the previous commit:
  that stops the agent being hijacked, this makes it report the attempt.
- comment-craft: how to write problem/fix/suggestion so a maintainer can act in
  one read, and what to cut.

pilot/cost_model.py — prices a review against published Claude and OpenAI rates
(fetched 2026-08-18). Prompt sizes are measured from the factory files rather
than guessed; per-tier workloads come from the tiering budgets. The model is
explicit about the thing that actually dominates an agent loop: the whole
conversation is resent every step, so caching moves ~2.3x of the bill.

Blended over a 5/35/55/5 mix with caching on: ~$0.61/PR on Opus 5 or GPT-5.6
Sol, ~$0.24 on Sonnet 5 or Terra, ~$0.12 on Haiku 4.5, ~$0.02 on Luna. At 350
PRs/month that's ~$212 / ~$85 / ~$43 / ~$8.50.

Tests: 101 -> 122.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01B11e8TZZxJyzHW7jj7KWUN
 2026-08-18 04:53:49 +00:00
Marcos 8c491a7626 harden(pilot): contain hostile PR content, bound the webhook, fix anchoring 
The reviewer runs an opencode agent with `bash: "*": allow` over a checkout of
the PR author's branch, and the pod holds a Gitea Write credential. Those two
facts had no wall between them.

Security
- _build_env now allow-lists the subprocess environment instead of inheriting
  it, so PRAGENT_BOT_TOKEN and WEBHOOK_SECRET never reach the agent. This was
  the live hole: a PR body or an AGENTS.md could ask the agent to `curl` the
  token out, and it had both the value and the tool.
- sanitize_workdir deletes author-controlled agent-instruction files from the
  checkout before opencode starts (AGENTS.md at any depth, CLAUDE.md,
  .cursorrules, a repo opencode.json/.opencode, copilot-instructions.md).
  opencode loads nested AGENTS.md as instructions, so a PR could otherwise ship
  its own system prompt. They are still reviewed, as data.
- The brief fences PR title/body and diff in --- UNTRUSTED --- markers under a
  trust-boundary preamble; the pragent agent, the three lens subagents and the
  review-methodology skill now treat injection attempts as a critical finding
  to report rather than an instruction to obey.
- .pr-review.json is read from the PR's base branch, not the head sha. Its
  `instructions` field is spliced into the reviewer's prompt, so head-ref
  reading let any author rewrite the reviewer's rules. Fields are length-capped.
- Untar rejects escaping symlinks, parent traversal, and writes through a
  planted symlink (tar-slip).
- The image runs as uid 10001 instead of root.

Robustness
- Bounded review concurrency (PRAGENT_MAX_CONCURRENT_REVIEWS, default 2). Each
  review forks an opencode process; a thread per delivery was a fork bomb on a
  burst of labels or Gitea retries.
- An in-flight (repo, index, sha) claim closes the check-then-act race in the
  sha-marker dedupe, where two deliveries a second apart both read "not yet
  reviewed" and both posted.
- Request bodies are capped before being read into memory.

Correctness
- parse_diff_anchors counts a whitespace-stripped blank context line. Skipping
  it desynced the new-line counter for the rest of the hunk and silently
  misplaced every later inline comment in that file.
- post_inline_review's body-only fallback folds the anchored findings into the
  body. It previously posted a summary saying "N inline comment(s) below" with
  no comments and no findings — losing them all on the one path that matters.
- fetch_pr_diff's files-endpoint fallback emits real a// b/ prefixes (so
  changed_files and the anchor parser work on it) and reports both HTTP statuses
  in its error instead of the same one twice.
- The CI workflow template pins PRAGENT_ENGINE=ollama; review_pr defaults to
  opencode, which does not exist on a Gitea Actions runner.

Tests: 68 -> 101, covering each of the above.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01B11e8TZZxJyzHW7jj7KWUN
 2026-08-18 04:44:44 +00:00
Marcos 087834565d feat(pilot): token-usage reporting gated by AI-USAGE label 
Add per-review + per-comment token accounting, surfaced only when a PR carries
the new AI-USAGE label (on top of the existing AI-REVIEW trigger).

opencode_review:
- run_opencode now uses `--format json`; parse_opencode_events reconstructs the
  assistant text from `text` events and sums tokens/cost/steps from every
  `step_finish` event (tolerant of noise / missing fields).
- run() measures duration_s around the opencode call and returns (text, usage).
- changed_files(diff) extracts the `+++ b/` paths; the brief now lists them
  under a "Changed files" focus block so the agent grounds findings in the
  diff's neighbourhood instead of unbounded whole-repo walks.

ai_review:
- format_usage_section renders a `## AI usage` block: measured totals
  (in/out/reasoning/cache/cost/steps/duration), the whole-repo scope note, and
  an attributed per-finding table. Per-comment counts are output tokens split by
  each finding's body weight — labelled "attributed" since one model pass
  produces all findings.
- inline_comment_body appends `🪙 ~N tok (X% · attributed output)` when
  attribution is present.
- review_pr gains report_usage; compute_attribution stashes _tok_attrib/_tok_pct.
- format_review_body inserts the usage section between summary and findings.

webhook_server:
- Fire on every pull_request action except `closed` (denylist, was an allowlist)
  — the AI-REVIEW gate + sha dedupe keep this safe.
- AI-USAGE label detection + PRAGENT_USAGE_ALWAYS env drive report_usage.

.opencode factory + review-methodology skill: new "Ground findings in context"
step — read callers/imports/sibling functions per changed file (1-3 files per
finding), no unbounded walks.

Tests: parse_opencode_events (text+usage sum, malformed tolerance, none-usage),
changed_files, compute_attribution math, inline 🪙 line, format_usage_section
totals/table/cost, format_review_body ordering. 68 passing.

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-08-18 04:15:11 +00:00
Marcos 76b6752f48 fix(review): language-tagged suggestion fence for Gitea syntax highlighting 
Gitea 1.26.x has no GitHub-style 'Apply suggestion' button — a ```suggestion
fence is just an unknown-language code block, so chroma does not highlight it
and there is no apply control. Switch inline_comment_body to wrap the suggested
fix in a fence tagged with the file's language (new _lang_for_path helper,
.java→java, .ts→typescript, .py→python, ...), so Gitea syntax-highlights the
code. No capability lost (there was never an apply button on this Gitea
version). Correct the docstrings/skills/README that wrongly claimed an
apply-button was rendered.

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-08-18 01:26:37 +00:00
Marcos 8912f6721b deploy: combined opencode image + k8s + docs 
- pilot/Dockerfile: python:3.12-slim + node 20 + opencode-ai@1.3.10 +
  ripgrep + pyright/typescript-language-server/eslint (npm) + ruff (pip).
  Factory + pilot scripts baked at /app. imagePullPolicy: Never (local
  import into microk8s containerd).
- .dockerignore: lean build context.
- ~/k8s/pragent-webhook.yaml: image pragent-webhook:opencode, emptyDir work
  at /tmp/pragent-work, env (PRAGENT_ENGINE, OPENCODE_MODEL, PRAGENT_FACTORY_DIR,
  PRAGENT_OPENCODE_BIN, PRAGENT_WORK_ROOT, PRAGENT_RTK_DIR='', timeout 540),
  resources 200m/512Mi -> 1500m/2Gi. Drops the ConfigMap scripts volume.
- pilot/README-webhook.md + .opencode/README.md: opencode engine section,
  build/import/apply steps, factory guide fixes (parse_review_output, steps).

Image builds (1.62GB, smoke-tested: opencode+LSPs+factory+env all present).
Import into microk8s containerd + apply pending (ctr needs sudo).

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-08-17 23:11:58 +00:00
Marcos 6e3a9eb5b0 feat: opencode review engine + .opencode factory 
Replace the single Python model-call reviewer with an opencode agent
factory. A primary 'pragent' agent reads a brief (title/body/diff/config/
prior reviews), inspects the checked-out repo, runs the repo's own linters
via bash, loads review-methodology + findings-schema skills, and emits a
{summary, findings} JSON with per-finding severity/path/line/problem/fix/
suggestion/reference. Dormant security/tests/perf subagent lenses fan out
only on large/risky diffs (lean by default).

pilot/opencode_review.py: fetches the repo archive at the head sha into a
temp workdir, writes .pragent/brief.md, drops the factory, runs
'opencode run --pure --agent pragent --dir <workdir>' headlessly. Isolates
HOME (shared, warmed), strips ANTHROPIC_* env (leaked host vars caused
ProviderModelNotFoundError), stdin=DEVNULL (opencode blocks on stdin),
maps the bare OLLAMA_MODEL to the provider-prefixed ref. No Gitea I/O —
ai_review.review_pr parses + anchors + posts (reuses all v2 logic/tests).

PRAGENT_ENGINE=opencode (default) selects it; =ollama keeps the legacy
direct-call path. Verified end-to-end: posts a real review with a summary
section, inline [CRITICAL]/[HIGH] comments + apply-able suggestions +
reference links, and the sha dedupe marker. 49 tests pass.

Co-Authored-By: Claude <noreply@anthropic.com>
 2026-08-17 23:01:59 +00:00