Material for MkDocs site (mkdocs.yml, optional extra `docs`) with Mermaid via
the superfences custom fence. New pages: overview, scanning (modes, quick
rules, Joern engine, priors, pre-push delta), the plane on ax (one task as a
sequence, golden snapshot, Run DAGs), memory (row kinds, write/read paths,
FileStore vs S3, verify at startup), memory and detection, and RustFS setup
(admin steps, complete agent policy, .env, refusal messages, Select limit).
The ops READMEs are included at build time; evaluation gains the population
lifecycle and the fold layout. tests/test_docs_site.py runs the strict build
when mkdocs is importable and checks Mermaid blocks and the RustFS page.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
README: "Configuring the HarnessX agentic plane" becomes "The agentic
plane (ax)" (ousast plane run|status|doctor|remember, per-task Model,
budget and egress, pointer to ops/ax/README.md, one tagged retirement
line); "The HarnessX self-improving cycle" becomes "The self-improving
cycle", and its MetaAgent paragraph is replaced by the memory proposer
(`ousast improve --memory`, provenance, train-on-test guard). The fusion
panel_model/decider_model lines and the [harnessx] spend caps are gone.
The README reference test now passes without its strict xfail.
docs/examples.md section 6 runs the plane; docs/threat-model.md describes
the per-task EgressPolicy, the usd/calls budgets and the start-request
credential path. RELEASE_NOTES.md gets an Unreleased entry: HarnessX
removed, the retired keys and their errors, the silent loss of the
second hunter for users who set [models] hunter, and the plane as the
agentic path.
Dated retirement notes (2026-09-30) head the requirements, design and
brief of harnessx-self-improving-rulesets, learning-harness,
three-stage-scan and openrouter-sast-harness, and follow the spec table
in steering/overview.md; history is unchanged. All tasks are checked, so
spec.json moves to implementation-complete.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The maintainer settled the conflict the group 2 review escalated: a detector
configuration has no skills set. The skill router belongs to the tool's earlier
shape, and a family's prompt, checklist, tools and counterexamples already carry
what a round evolves.
The README described the project as an editor-agent harness whose skills steer
it, and pointed users at the maintainer's spec directory. The tool is a CLI now
and the agent integrations are optional, so the opening says that, the skills
section describes what it actually is, and the spec pointer is gone from the
user-facing text.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
Review rounds 3-5 remediations (Req 5, 7).
- ousast improve resolves candidates from the target's calibration dir,
then the working directory's (where `mechanisms export` writes), and
admits into <target>/.openultrasast/calibration/mechanisms.jsonl,
where a scan of that target reads; --mechanism-candidates,
--mechanism-store, --no-mechanisms; --dry-run redirects the store to
scratch; accepted rounds print admit/retract <id>.
- run_improvement threads the store paths; RoundOutcome carries the
mechanism edits; reverted mechanism keys are blocked outright; a
no-gain admission is rejected as mechanism_no_gain; a retraction may
name an admitted record that left the candidate set.
- leave-one-out forwards variant-search degradations and pins the
containment and label rules; mechanisms export defaults to the
candidates file so it never re-admits a tombstone.
- design §Lever rewritten to the implemented gate; README and docs show
export -> improve -> scan.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
Task 8.4 (Req 10.6, 5.1).
- harvest.merge_recipes appends recipes by name and never rewrites
existing rows.
- vibe-py/build_recipes.py --pointers: the 40 LLM-generated repositories
without a license become vendored = false rows (80 pairs, agent,
seeded) appended to recipes.toml; unlicensed human repos stay skipped.
- agent-vfc/build_recipes.py --from ... --pointers [--cache]: unlicensed
agent-authored fixes become title-tier pointer rows whose function
label is derived from the cached excerpt (30 added from a fresh
662-candidate search); TOML booleans rendered correctly.
- catalogs regenerated: vibe-py 115 rows (35 vendored + 80 pointer),
agent-vfc 59 (29 + 30); no excerpt is vendored for any pointer row.
- `pairs --slice vibe-py --pointers` scores both provenances (human 35,
agent 80); the default run skips 80 pairs with pointer_pair_skipped;
suite and gates unchanged. README/docs name the nightly command.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
Regex inventory stays the proposer. MAP attaches promote/demote/unadjudicated/coverage
from intra-file taint (tree-sitter when a grammar parses, Python ast as last resort).
Deep sandboxes promotions only, ordered by the existing heuristic ranker plus optional
OpenRouter mechanism recall. The SAST pair slice scores overlay outcomes; the stage-1
detection gate and local pair gate stay inventory-only.
A zero-dependency MCP server over stdio (newline-delimited JSON-RPC 2.0) for
OpenCode/IDE integration, exposing only stable project-level operations.
- mcp.py: McpServer (pure handle() dispatch) + serve() stdio loop, stdlib-only.
Ten tools: openultrasast.scan/status/findings/get_finding/evidence/artifacts/
benchmark/explain/propose_patch/export_report. scan/benchmark run the bounded
analysis pipeline; NO tool accepts a free-form command — no shell, Docker, or
internal hunter tools are exposed. propose_patch degrades visibly (patch oracle
is a later phase). initialize/tools/list/tools/call/ping handled; notifications
get no response; errors surface as JSON-RPC errors instead of crashing the loop.
- cli: `ousast mcp` subcommand launches the stdio server (lazy import → keeps the
mcp↔cli cycle one-directional).
- tests/test_mcp.py: tool listing is exactly the narrow surface, surface-safety
(no shell/exec/command tool), scan→status→findings→explain→evidence flow,
export_report, propose_patch degradation, and the stdio loop round-trip.
- README "MCP server" section; openrouter-sast-harness Phase 12 checked off.
Verified end-to-end over real stdio (initialize → tools/list → scan). 179 passed,
4 skipped; ruff + mypy clean; detection gate PASS.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
Add a [harnessx] config block so the agentic plane can be steered from
openultrasast.toml, and make the LLM provider selectable (the hunter and verifier
previously hardcoded AnthropicProvider).
- config.HarnessxConfig: provider ("anthropic"|"openai"|"litellm", default
anthropic), max_cost_usd (2.0), token_threshold (120000); parsed from [harnessx].
- harness_ext.build_provider: single lazy, capability-guarded provider factory.
The provider name is validated before any import, so an unknown choice fails with
a clear ValueError even when the extra is absent; each provider reads its own
standard key env var (openai -> OPENAI_API_KEY, anthropic -> ANTHROPIC_API_KEY).
- HxScanOrchestrator and verify_findings_dispatch take a provider and route through
build_provider; cli threads config.harnessx.{provider,max_cost_usd,token_threshold}
into both the hunter and the verifier.
- README: "Configuring the HarnessX agentic plane" section (install, models,
provider, budgets, fallback/degradation).
Test isolation: convert the "harnessx not in sys.modules" import-guards to a
hermetic subprocess fixture (tests/conftest.py assert_cold_of_harnessx) and
simulate extra-absent in the CLI dispatch tests, so the suite is deterministic
whether or not the optional extra is installed (it now is, locally). Verified the
OpenAI path constructs end-to-end (build_provider -> OpenAIProvider; orchestrator
-> Harness) with the budget threaded through.
137 passed, 3 skipped; ruff + mypy clean; detection gate PASS.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
Expose the bounded, gated self-improvement loop as a first-class subcommand so it
can be steered from the command line / opencode.
- `ousast improve <manifest>` resolves the target from the benchmark manifest,
runs the loop to convergence, and writes accepted edits to the loop-owned ledger
at <target>/.openultrasast/calibration/rule_policy.json — exactly where `scan`
and `benchmark` read it, so a subsequent scan of that target automatically
picks up the improved ruleset (the loop closes end-to-end).
- Flags: --max-rounds, --recall-floor, --fp-ceiling, --ledger, --journal,
--ruleset-dir, and --dry-run (runs against a throwaway ledger, touches nothing).
- Per-round output: reason, recall/fp/score deltas, and the edits applied.
- tests/test_cli_improve.py: accept path writes the loop-owned ledger (noisy rule
auto-shadowed), --dry-run never touches it, missing manifest fails loudly.
- README: quickstart entry + a "Rule-level loop: ousast improve" subsection
documenting the bounded levers, hard acceptance gate, and the HarnessX MetaAgent
as the optional proposer over the same gated machinery.
131 passed, 3 skipped; ruff + mypy clean; detection gate PASS.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
CI: the dagger job repeatedly failed (and once hung 10 min) pulling the engine
image from registry.dagger.io. Pin the dagger CLI to 0.21.7 (matching dagger-io
and the SDK's CLI_VERSION so the engine tag is deterministic), pre-pull
registry.dagger.io/engine:v0.21.7 with a dependency-free retry loop (5 attempts,
90s/pull, 20s backoff) so the action's `docker image inspect` finds it cached and
skips its own flaky pull, and add a 20-minute job timeout so a stalled pull can
no longer hang the run. The canonical `checks` job is unchanged.
Docs: add a "Project scores and central CWE policy" README section documenting
the implemented Phase 1 — central verycode CWE policy, policy-governed severity
(one CWE = one severity), the fail-loud invariant, the 0-100 project score and
two-condition advisory-first gate, the score.json/manifest artifacts, and the
CWE-120 -> CWE-121 remap.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
Close the HarnessX self-improving loop without an agent in the loop. Every scan
now feeds its verifier outcomes back into the next scan's ranking:
- New `calibrate` stage (after rank, before findings) loads a persistent ledger
of scoped false-positive learnings and demotes every previously-rejected scope
(`calibrate_rankings`), writing `calibration/applied_calibrations.json`.
- New `record_calibration` stage (after verify) converts this run's non-accepted
verifier outcomes into scoped `FalsePositiveLearning` records
(`learnings_from_verifications`) and merges them into
`.openultrasast/calibration/false_positive_learnings.json`, de-duplicated by
finding ID so a repeat rejection does not compound without bound.
- Lower the calibration floor (MIN_CALIBRATED_PRIORITY = 0.1) so accumulated
rejections can demote a scope below the natural ranking minimum.
Demotion is scoped and reversible: a rejection in one path never touches an
accepted finding in another, and priority is demoted rather than the finding
deleted so the audit trail explains every downgrade. First run is a no-op
(empty ledger), so existing single-run behavior is unchanged.
Adds tests/test_pipeline_calibration.py (two-run demotion, order-independent),
documents the realized loop in the README, and checks off the
standard_security_harness milestone in tasks.md.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
- OpenUltraSAST is driven from the command line (ousast CLI, or OpenCode invoked
on the repo running the harness for you); show both.
- Mark the kiro-* skills and AGENTS.md as maintainer-only SDLC tooling, not part
of using OpenUltraSAST; drop them from the user-facing skill list.
- State that OpenCode is the agent steering the HarnessX self-improving cycle
today (reads verifier/benchmark signals, applies scoped calibration via the
triage skill, re-runs the gate); autonomous in-pipeline feedback is the next
milestone.
- Remove a duplicated Fusion section.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
Expand the README with: how to run the per-language benchmarks and the latest
measured results (C/C++ 93.3%, Python 93.3%, JavaScript 92.3%, Java 100%;
overall 93.6% recall, 0% false positives); the OpenCode skills, the ultra
(OpenUltraCode) fix lifecycle, and fusion deepening; how a false positive is
eliminated via the evidence-ladder verifier and scoped calibration; how a false
negative becomes a benchmark calibration record routed to a next-improvement
candidate; and how the HarnessX self-improving cycle is realized. Maturity is
marked (implemented / primitive / roadmap) to stay accurate to the current gate.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
