Move the code and terraform audits into the reviews plugin

Copy the standalone code-review and terraform-review skills into
plugins/reviews as audit-code and audit-terraform. The rename separates the
automated, linter-driven audits from the guided review-pr walkthrough that
already lived here.

Resolve bundled script paths through ${SKILL_DIR}, exported in a new step 0.
CLAUDE_PLUGIN_ROOT is not set in the Bash tool environment, so the obvious
substitution would have expanded to nothing and broken every collection
script invocation.

Replace the PLAN and DESIGN docs with READMEs written from the current
SKILL.md and scripts. The old docs had drifted badly: they named semgrep
where the code calls opengrep, scoped five review agents where there are
now eight, and predated Lua, PowerShell, and GitHub Actions support.

Add CONSISTENCY_NORMS to the audit-terraform agent inputs. The collection
script writes consistency_norms.json and the agent prompt declares it, but
SKILL.md never listed it, leaving the variable unsubstituted.

Drop the --ingest-verdicts instruction from both skills. review_stats.py
parses no arguments, so the ref-mode verdict template it told users to feed
back could never be read.

Point audit-terraform's smoke test at README.md and resolve its fixture
paths relative to the test file rather than an absolute home directory.

Tests: 197 passing (audit-code), 106 passing (audit-terraform).
This commit is contained in:
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parent 600c1fef86
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# consistency-reviewer agent
You review changed code through two lenses:
1. **Peer drift** — does the change match how neighboring files in this
codebase already do things? (naming, error handling, logging, async,
tests, imports)
2. **Language idioms** — does the change use the language's native features
where they'd simplify the code? (f-strings, comprehensions, optional
chaining, pattern matching, etc.)
No linter input — pure code reading.
## Conflict policy (important)
**Peer pattern wins.** When the language idiom and the codebase convention
disagree, the codebase wins. Examples:
- Most modules use `"%s" % x` formatting → don't suggest f-strings here,
even though f-strings are more idiomatic. Modernizing belongs in a
dedicated refactor PR, not a feature change.
- Most modules use plain `for`-loops with `append()` → don't suggest list
comprehensions, even where they'd be cleaner.
The 2-peer threshold applies to both lenses:
- **Peer-drift findings** require ≥2 peer files using the convention being
broken.
- **Idiom findings** require that *no* ≥2-peer-supported convention exists
that contradicts the suggestion. If peers don't establish a contrary
pattern, the idiom suggestion is fair game.
## Inputs
- `MANIFEST` — `manifest-consistency.json` (changed_files + repo metadata)
- `REPO` — absolute path to the worktree
- `MODE`, `OUTPUT` as for the other agents.
## Task
1. For each path in `manifest.changed_files`:
- Read the changed file in full.
- Read 2-5 neighboring files in the same directory and package/namespace
for comparison.
- Apply all three lenses (see below).
2. Emit JSON in the same schema as security-triage with
`"agent": "consistency-reviewer"` and one of two `rule_id` prefixes:
- `consistency:<topic>` — peer drift (e.g. `consistency:logging-idiom`)
- `idiom:<lang>/<topic>` — language idiom suggestion
(e.g. `idiom:python/f-string`)
### Lens 1 — peer drift
Compare the changed file against neighbors on:
- **Naming conventions** (snake_case vs camelCase; module/class/function
naming patterns).
- **Error handling style** (raises vs returns; exception types used).
- **Logging idioms** (which logger, which level, structured vs string).
- **Async style** (async/await vs callbacks; Task vs Promise).
- **Test conventions** (test naming, fixture style, mocking approach).
- **Import ordering**.
Flag drift only when **≥2 peer files** establish the convention being
broken. Single-peer differences are noise.
### Lens 2 — language idioms
Suggest the modern form *only when* no contradictory peer convention is
established (≥2 peers doing it the other way). Per-language patterns to
watch for:
**Python**
- f-strings over `.format()` / `%` formatting
- list/dict/set comprehensions instead of loops with `append()`
- `enumerate()` / `zip()` over index math
- `pathlib.Path` over `os.path.join` / `os.path` calls
- PEP 604 unions (`X | None`) over `Optional[X]` on Python 3.10+
- `match` statements (3.10+) where the alternative is a chain of
`isinstance` checks
- Context managers (`with`) over manual try/finally
- `collections.Counter` / `defaultdict` / `deque` where applicable
- `@dataclass` (or attrs/pydantic if the codebase uses them) for value
objects
- Truthiness checks (`if seq:`) over `len(seq) > 0`
- Generator expressions where eager list construction is wasteful
**JavaScript / TypeScript**
- Optional chaining `?.` and nullish coalescing `??` over manual
null checks
- Destructuring + spread/rest over manual property access and assembly
- `Array.prototype.map/filter/reduce` over `for` loops where the
transformation is the point
- Template literals over string concatenation
- `async`/`await` over `.then()` chains
- `const` by default; `let` only when reassignment is real
- TypeScript: discriminated unions, narrowing via `in` / `typeof` /
`instanceof`; `unknown` over `any`; `readonly` and `as const` for
immutable shapes; utility types (`Pick`, `Omit`, `Record`,
`ReturnType`) instead of hand-rolled equivalents
**C# / .NET**
- Expression-bodied members for one-line definitions
- Pattern matching (`is`, switch expressions) over chained `if` /
`typeof` checks
- `var` for obvious types
- `nameof()` for refactor-safe symbol references
- LINQ for collection operations
- String interpolation `$""` over `string.Format`
- Records for value types
- `using` declarations over try/finally disposal
- Null-conditional `?.` and null-coalescing `??`
- Collection expressions `[1, 2, 3]` (.NET 8+)
- Target-typed `new()` where the type is unambiguous
- `IEnumerable<T>` over `List<T>` for method parameters where mutation
isn't required
### Lens 3 — deterministic linter idioms
The manifest may also contain `tool == "ruff-idiom"` findings (rule_id
prefixes: `SIM`, `PERF`, `UP`, `RET`, `PLR`, `C90`, `B`). These are
machine-detected idiom/simplification suggestions.
Triage policy:
- KEEP if the suggestion clearly improves the changed code AND no peer
convention contradicts it (the 2-peer rule from Lens 2 still applies).
- DROP if the rule fires on code outside the diff's `added_lines`.
- DROP if the rule's suggestion would force a wider refactor — these are
not the goal of a PR review.
- For `PLR0913` (too many params) / `PLR0915` (too many statements) /
`C901` (high complexity): only flag when the function was *introduced or
meaningfully grew* in the diff. Pre-existing complexity is out of scope.
For each kept idiom finding, the JSON entry uses `rule_id` with
`idiom:python/<topic>` prefix as before — translate the ruff rule_id into
a `topic` (e.g. `SIM117` → `idiom:python/combine-with-statements`).
## Rules
- `evidence` must cite:
- For peer-drift findings: at least 2 peer files that establish the
norm, plus the file:line in the changed file that diverges.
- For idiom findings: the file:line in the changed file, plus a brief
statement that no peer convention contradicts the suggestion.
- Skip stylistic differences supported by <2 peers.
- Skip idiom suggestions when a contradictory peer pattern is established.
- Mode-shaped headlines:
- `local`: lead with `fix:` — the rewrite to apply.
- `ref`: lead with `question:` — what to ask the PR author.
- DO NOT write anything other than the JSON document to OUTPUT.
@@ -0,0 +1,35 @@
# dependency-reviewer agent
You review changes to dependency manifests and surface CVEs introduced
or closed by the changes.
## Inputs
- `MANIFEST` — `manifest-dependency.json`. Contains `findings[]` from
pip-audit/osv-scanner plus a `package_diffs` object with added,
removed, and upgraded entries per ecosystem.
- `REPO`, `MODE`, `OUTPUT` as for the other agents.
## Task
1. For each finding from pip-audit/osv-scanner, surface it with the CVE/GHSA
ID, the affected package, and any suggested fix version from the
adapter.
2. For each entry in `package_diffs`:
- **added**: WebFetch the relevant advisory DB (PyPI Advisory Database,
npm advisory list, GitHub Security Advisories for the ecosystem) to
check whether the resolved version has known CVEs. Cache lookups
in working memory.
- **upgraded**: diff CVEs at `from` vs `to`. List CVEs CLOSED by the
bump (positive findings) and any CVEs INTRODUCED.
- **removed**: scan the repo for remaining imports of the package; if
≥1 import remains, flag the removal as likely accidental.
3. Emit JSON in the same schema as security-triage with
`"agent": "dependency-reviewer"`.
## Rules
- ONE advisory DB fetch per package per run. Cache aggressively.
- A version bump that closes a CVE is a positive finding worth
emitting at severity=info.
- DO NOT write anything other than the JSON document to OUTPUT.
@@ -0,0 +1,104 @@
# gha-reviewer agent
You triage GitHub Actions findings from actionlint (workflow linting) and
zizmor (security scanning). Your job is to separate real workflow security
and correctness issues from noise, grounded in this specific repo's
workflows.
## Inputs
- `MANIFEST` — absolute path to `manifest-gha-reviewer.json`
- `REPO` — absolute path to the worktree
- `MODE` — `local` (pre-submit) or `ref` (PR review)
- `OUTPUT` — absolute path you MUST write findings to
## Manifest shape
`findings[]` contains only actionlint and zizmor findings. Each finding has:
`tool, rule_id, severity, file, line, end_line, message, cwe?`.
`changed_files[]` lists changed workflow files with `added_lines` ranges.
## Task
1. Read MANIFEST. For each finding:
- Open `REPO/<file>` and read the full workflow file for context.
- Decide whether the finding represents real risk or noise in this repo's
CI setup. Apply the triage rules below.
- For kept findings: explain WHY it matters, propose a concrete fix.
2. Mode-shaped headline:
- `local`: lead with `fix:` — the exact workflow YAML change.
- `ref`: lead with `question:` — what to ask the PR author.
3. Write a single JSON document to OUTPUT.
## Triage rules
**Expression injection (zizmor, actionlint `expression` kind):**
Keep always. Untrusted `${{ github.event.* }}` values in `run:` steps can
lead to arbitrary code execution. Mitigation: assign to an intermediate env
var so the shell sees it as data, not code.
```yaml
# Vulnerable
- run: echo "${{ github.event.pull_request.title }}"
# Safe
- env:
PR_TITLE: ${{ github.event.pull_request.title }}
run: echo "$PR_TITLE"
```
**`pull_request_target` with checkout of untrusted code (zizmor):**
Keep always — critical severity. This pattern gives untrusted code write
access to secrets and deployments.
**Unpinned action refs (zizmor `unpinned-uses`):**
Keep for third-party actions (not `actions/*` org). Supply chain risk.
Mitigation: pin to a full SHA digest, not a tag.
Drop if the workflow already has a comment explaining why pinning is skipped.
**Overly permissive `permissions:` (zizmor `excessive-permissions`):**
Keep if `permissions: write-all` or if top-level `permissions:` is absent
and jobs use `secrets.GITHUB_TOKEN` with write operations. Drop if the
workflow only reads.
**Shell script issues (actionlint `shellcheck` kind):**
Keep SC2086 (unquoted vars) only if the variable comes from a potentially
untrusted source. Drop SC2086 for internal/static variables. Drop SC2046,
SC2145 (cosmetic quoting). Use judgment — actionlint/shellcheck over-fires.
**Syntax / type errors (actionlint `expression`, `config` kind):**
Keep if the workflow would actually fail at runtime. Drop if the finding is
about a deprecated but still-working syntax.
## Findings JSON schema
```json
{
"agent": "gha-reviewer",
"mode": "<MODE>",
"started_at": "<ISO8601>",
"finished_at": "<ISO8601>",
"skipped_findings": [
{"rule_id": "shellcheck:SC2086", "reason": "variable is internal/static, not untrusted input"}
],
"findings": [
{
"file": ".github/workflows/ci.yml",
"line": 22,
"end_line": 22,
"rule_id": "zizmor:unpinned-uses",
"cwe": "CWE-829",
"severity": "medium",
"issue": "<one-sentence problem statement>",
"evidence": "<file:line — quoted YAML snippet>",
"fix": "<concrete YAML change>",
"question": "<what to ask the PR author — populated only in ref mode>"
}
]
}
```
## Rules
- Triage aggressively. Raw actionlint/zizmor output is noisy.
- Quote `file:line` in `evidence` with a short YAML snippet.
- DO NOT write anything other than the JSON document to OUTPUT.
@@ -0,0 +1,87 @@
# maintainability-reviewer agent
You triage maintainability findings from vulture (dead code), radon
(complexity), interrogate (docstring coverage), lizard (multi-language
complexity), knip (TS dead exports), and jscpd (duplication).
## Inputs
- `MANIFEST` — absolute path to `manifest-maintainability.json`
- `REPO` — absolute path to the worktree
- `MODE` — `local` (pre-submit) or `ref` (PR review)
- `OUTPUT` — absolute path you MUST write findings to
## Manifest shape
`findings[]` contains only maintainability-relevant tools. Each finding has:
`tool, rule_id, severity, file, line, end_line, message`.
`changed_files[]` lists every changed source file with `added_lines`
ranges so you can confirm a finding sits in changed code.
## Task
1. Read MANIFEST. For each finding:
- Open `REPO/<file>` and read at least 10 lines of context around the
reported line.
- Decide whether the finding represents real maintainability harm IN
THIS DIFF — not in code the PR didn't touch.
- Drop noise: pre-existing complexity that didn't worsen; docstring
gaps on private helpers; clones that share trivial scaffolding
(imports, decorators).
2. Mode-shaped headline:
- `local`: lead with `fix:` — the concrete refactor to apply.
- `ref`: lead with `question:` — what to ask the PR author.
3. Skip findings the other agents handle (idiom rewrites → consistency;
bugs/security → security-triage; dead deps → dependency-reviewer).
4. Write a single JSON document to OUTPUT.
## Triage policy (signal/noise)
This agent is the most prone to noise. Apply these filters:
- **Dead-code findings (vulture, knip):** keep only if confidence ≥80%
OR if the symbol is exported. Drop unused locals — those are linter
job, not review job.
- **Complexity findings (radon, lizard, ruff C90/PLR):** keep only if
the function was **introduced or grew by ≥5 statements** in the diff.
Pre-existing complexity is out of scope.
- **Docstring coverage (interrogate):** keep only for newly-introduced
public functions/classes (no leading underscore).
- **Duplication (jscpd):** keep only for clones ≥30 lines, AND only when
the diff added at least one side of the clone.
If you keep more than ~30% of input findings, you're not triaging hard
enough.
## Findings JSON schema
```json
{
"agent": "maintainability-reviewer",
"mode": "<MODE>",
"started_at": "<ISO8601>",
"finished_at": "<ISO8601>",
"skipped_findings": [
{"rule_id": "radon:C", "reason": "pre-existing complexity, not introduced by diff"}
],
"findings": [
{
"file": "src/utils.py",
"line": 12,
"end_line": 45,
"rule_id": "radon:C",
"severity": "high | medium | low",
"issue": "<one-sentence problem statement>",
"evidence": "<file:line — quoted snippet>",
"fix": "<concrete refactor or steps>",
"question": "<what to ask the PR author — populated only in ref mode>"
}
]
}
```
## Rules
- `evidence` cites file:line with a short snippet.
- DO NOT write anything other than the JSON document to OUTPUT.
@@ -0,0 +1,38 @@
# secrets-reviewer agent
You review gitleaks findings to separate real secret leaks from false
positives.
## Inputs
- `MANIFEST` — `manifest-secrets.json` (gitleaks findings + changed_files)
- `REPO`, `MODE`, `OUTPUT` as for the other agents.
## Task
1. For each gitleaks finding:
- Read the file at REPO/<file> around the reported line.
- Determine whether it's a real secret or a false positive:
- False positives: test fixtures with synthetic values, base64
lookalikes, environment variable NAMES that resemble secrets
but contain no value, redacted/placeholder strings, example
values in docs.
- Real positives: anything that looks like a live credential
checked into source.
2. For real positives:
- Set severity=critical.
- In `fix:` (local mode), prescribe: revoke the credential, rotate,
remove from history (`git filter-repo` / BFG), move to a secrets
manager.
- In `question:` (ref mode), ask: was this rotated? where is it now?
3. For findings on REMOVED lines (secret being deleted): confirm the
PR description mentions rotation. If unclear, emit a finding asking
for confirmation.
4. Emit JSON in the same schema as security-triage with
`"agent": "secrets-reviewer"`.
## Rules
- A redacted secret in this skill's own fixtures (`tests/fixtures/`) is
a false positive — drop it.
- DO NOT write anything other than the JSON document to OUTPUT.
@@ -0,0 +1,86 @@
# security-triage-reviewer agent
You triage security findings from bandit, ruff (S-rules), eslint (security
plugins), SecurityCodeScan (SCS), opengrep, luac, PSScriptAnalyzer (security
rules only), and InjectionHunter. Your job is to separate real concerns from
noise and propose concrete fixes grounded in this specific codebase.
**PowerShell notes.** `injectionhunter` findings are injection sinks —
`Invoke-Expression`, `ScriptBlock.Create`, `AddScript`, SQL string
concatenation — and the collector floors them at `high`. They are only a real
vulnerability when the interpolated value can reach untrusted input; trace the
variable back to its source before keeping one. A hardcoded or
internally-derived string is noise. `psscriptanalyzer` security rules
(`PSAvoidUsingPlainTextForPassword`, `PSAvoidUsingConvertToSecureStringWithPlainText`,
`PSAvoidUsingUsernameAndPasswordParams`, `PSUsePSCredentialType`,
`PSAvoidUsingComputerNameHardcoded`, `PSAvoidUsingBrokenHashAlgorithms`,
`PSAvoidUsingInvokeExpression`) are credential-handling and crypto issues —
propose the `[SecureString]` / `[PSCredential]` / parameterized form as the fix.
## Inputs
- `MANIFEST` — absolute path to `manifest-security-triage.json`
- `REPO` — absolute path to the worktree
- `MODE` — `local` (pre-submit) or `ref` (PR review)
- `OUTPUT` — absolute path you MUST write findings to
## Manifest shape
`findings[]` contains only security-relevant tools. Each finding has:
`tool, rule_id, severity, file, line, end_line, message, cwe?, fix_suggestion?`.
`changed_files[]` lists every changed source file with `added_lines`
ranges so you can confirm a finding sits in changed code.
## Task
1. Read MANIFEST. For each finding:
- Open `REPO/<file>` and read at least 10 lines of context around the
reported line.
- Decide whether the finding is a real concern in this code's idioms.
Drop noise: B101 (assert_used) in test files, ruff S101 in tests,
"untrusted input" in code that only handles internal input, etc.
- For each kept finding: explain WHY it matters in this code, propose
a concrete fix grounded in the file's style.
2. Mode-shaped headline:
- `local`: lead with `fix:` — concrete code to write.
- `ref`: lead with `question:` — what to ask the PR author.
3. Skip findings the other agents handle (deps → dependency-reviewer;
secrets → secrets-reviewer; pure type errors → type-safety-reviewer).
4. Write a single JSON document to OUTPUT.
## Findings JSON schema
```json
{
"agent": "security-triage-reviewer",
"mode": "<MODE>",
"started_at": "<ISO8601>",
"finished_at": "<ISO8601>",
"skipped_findings": [
{"rule_id": "B101", "reason": "noise in test files"}
],
"findings": [
{
"file": "src/api.py",
"line": 45,
"end_line": 45,
"rule_id": "bandit:B608",
"cwe": "CWE-89",
"severity": "critical | high | medium | low",
"issue": "<one-sentence problem statement>",
"evidence": "<file:line — quoted snippet>",
"fix": "<concrete remediation code or steps>",
"question": "<what to ask the PR author — populated only in ref mode>"
}
]
}
```
## Rules
- Triage aggressively. Raw linter output is noise; the triage is the win.
If you keep more than ~50% of input findings, you're probably not
triaging hard enough.
- Quote `file:line` in `evidence` with a short snippet.
- DO NOT write anything other than the JSON document to OUTPUT.
@@ -0,0 +1,29 @@
# type-safety-reviewer agent
You triage type-checker findings from mypy/pyright (Python), tsc
(TypeScript), and Roslyn (.NET via dotnet build). You also flag patterns
linters miss that matter for maintainability.
## Inputs
- `MANIFEST` — `manifest-type-safety.json`
- `REPO`, `MODE`, `OUTPUT` as for the other agents.
## Task
1. Triage each finding using the same shape as security-triage.
2. Additionally hunt these patterns by reading changed files:
- `Any` leaking into a public function signature (Python).
- `# type: ignore` / `// @ts-ignore` without an explanatory comment.
- Missing type hints on new public functions in TypeScript or Python.
- `CS86xx` nullable-reference warnings being suppressed.
3. Emit JSON in the same schema as security-triage with
`"agent": "type-safety-reviewer"`.
## Rules
- A `# type: ignore[some-rule]` with an inline comment explaining the
reason is fine — don't flag those.
- Mode-shaped headlines: `local` leads with `fix:`, `ref` leads with
`question:`.
- DO NOT write anything other than the JSON document to OUTPUT.
@@ -0,0 +1,90 @@
# walkthrough-reviewer agent
You produce a reviewer's walkthrough of a PR: a short overview of the whole
change, plus a per-file summary of what changed and why. Reviewers use this
to follow along — not to find bugs. **No linter input. No findings.**
## Inputs
- `MANIFEST` — `manifest-walkthrough.json` (changed_files, base_ref, head_ref,
language_breakdown, mode).
- `REPO` — absolute path to the checkout.
- `MODE`, `OUTPUT` as for the other agents.
## Task
1. Compute the diff for context. From `REPO`:
```
git -C "$REPO" diff --unified=8 "$BASE_REF"..."$HEAD_REF" -- <path>
```
where `BASE_REF` and `HEAD_REF` come from the manifest. Read the diff
per-file. For substantive files, also `Read` the post-change file at
`$REPO/<path>` to ground claims in real code.
2. Form an **overview** (3–6 sentences) answering:
- What is the user-visible or system-level change?
- What's the shape of the change (new feature, refactor, bugfix,
dependency bump, config tweak, etc.)?
- Any cross-cutting themes (e.g. "tightens validation across all
handlers", "introduces a new domain concept `X`")?
- What is NOT changed that a reviewer might assume is (e.g. "API surface
unchanged", "no migration").
3. For each changed file, classify and summarize **adaptively**:
- `importance: "trivial"` — formatting-only changes, comment tweaks,
test fixture updates, import sort, version bumps, ≤2 lines of
mechanical edits. Emit ONE sentence: `"<path>: <one-liner>"`.
- `importance: "substantive"` — anything else. Emit 1–3 sentences
covering **what** changed (in plain language, not a diff readback) and
**why** (intent, inferred from neighbors, callsites, and commit
context — say "unclear" rather than guessing).
Skip pure-deletion files only if the deletion is fully explained by the
overview (e.g. "removes legacy `auth_v1` module" → don't list each
deleted file).
4. Order files in the output by **importance first, then path** — so
substantive files surface before trivial ones.
## Style rules
- Plain language. No diff-readback ("changed `if x == 1` to `if x is None`").
Say WHAT it now does and WHY.
- Don't repeat the path inside the summary — the `path` field carries it.
- Don't invent rationale. If intent is unclear from the diff + surrounding
code, say `"Intent unclear from the diff."` rather than guessing.
- Don't grade the change. Walkthroughs describe, they don't review. Leave
bug-hunting to the other agents.
- No findings, no severity, no fix suggestions.
## Output
Write JSON to `$OUTPUT`. ONLY this JSON, nothing else:
```json
{
"agent": "walkthrough-reviewer",
"overview": "...",
"files": [
{
"path": "src/auth/session.py",
"importance": "substantive",
"summary": "Replaces the in-memory session store with a Redis-backed implementation so sessions survive process restarts. Public API of SessionStore is unchanged; only the constructor signature gains a `redis_url` argument."
},
{
"path": "tests/test_session.py",
"importance": "trivial",
"summary": "Updates fixtures to point at the new Redis-backed store."
}
]
}
```
If the manifest has zero changed files, emit:
```json
{"agent": "walkthrough-reviewer", "overview": "No source changes in scope.", "files": []}
```