Audit Claims

Audit Claims Skill

Perform a two-phase citation integrity audit on an open GitHub research PR using parallel subagents. Phase 1 extracts claims by report section; Phase 2 matches each claim against available evidence and generates findings. Posts inline review comments and emits a verdict for recipe routing.

Arguments

/autoskillit:audit-claims

• worktree_path — Absolute path to the research worktree (skill derives

feature_branch from git rev-parse --abbrev-ref HEAD inside it)

• base_branch — The base branch the PR targets (e.g., "main")
• pr_url — Explicit PR URL passed by the recipe (avoids re-discovering the PR)

When to Use

• Called by the research recipe orchestrator after review_research_pr
• Both read-only gates complete before any resolution step begins
• Can be invoked standalone to audit citation integrity for any open research PR

Critical Constraints

NEVER:

• Create files outside {{AUTOSKILLIT_TEMP}}/audit-claims/
• Approve a PR that has changes_requested findings
• Post review comments when gh is unavailable — output verdict=approved and exit 0
• Review files outside the PR diff — scope all audit to diff content only
• Modify any source code
• Run deterministic diff annotation (claim positions are report-level, not line-level)
• Generate findings for experimental claims — they are self-evidencing by definition
• Run subagents in the background (run_in_background: true is prohibited)

ALWAYS:

• Use the explicit pr_url argument instead of re-discovering via gh pr list
• Output verdict= on the final line
• Exit 0 in all normal cases; verdict drives recipe routing via on_result, not exit code
• Exit non-zero only for unrecoverable errors (e.g., gh CLI truly unavailable after graceful degradation)
• Use model: "sonnet" when spawning all subagents via the Task tool
• Deduplicate findings by (file, line) pairs before posting

Workflow

Step 0: Validate Arguments

Parse three positional arguments: worktree_path, base_branch, pr_url.

Derive feature_branch:

if [ -d "$worktree_path" ]; then
  feature_branch=$(git -C "$worktree_path" rev-parse --abbrev-ref HEAD 2>/dev/null || echo "")
else
  echo "Error: worktree_path '$worktree_path' does not exist or is not a directory" >&2
  exit 1
fi

If pr_url is missing or positional args are insufficient, abort with: "Usage: /autoskillit:audit-claims "

Step 1: Use the Explicit PR URL

Parse pr_number from pr_url (last path segment).

Get owner/repo (must run inside the worktree to resolve the correct repository):

gh repo view --json nameWithOwner -q .nameWithOwner -C "$worktree_path"

If gh is unavailable or not authenticated:

• Log "gh unavailable — skipping citation audit"
• Output verdict=approved
• Exit 0 (graceful degradation)

Step 2: Get PR Diff

mkdir -p {{AUTOSKILLIT_TEMP}}/audit-claims
gh pr diff {pr_number} > {{AUTOSKILLIT_TEMP}}/audit-claims/diff_{pr_number}.txt

Save the diff to {{AUTOSKILLIT_TEMP}}/audit-claims/diff_{pr_number}.txt (relative to the current working directory).

Do NOT run deterministic diff annotation — claim positions are report-level, not line-level. Subagents use section structure, not line markers.

Step 3: Two-Phase Claim Analysis

Phase 1 — Claim Extraction (parallel subagents by report section)

Divide the diff by top-level markdown section: ## Executive Summary, ## Results, ## Methodology, ## Discussion, ## Limitations, and any other top-level ## section.

Launch one Task tool subagent (model: "sonnet") per section containing + diff lines. Each subagent returns a JSON array of extracted claims:

[{
  "file": "research/report.md",
  "line": 42,
  "claim_text": "Our method reduces latency by 40% compared to baseline X",
  "claim_type": "experimental|external|methodological|comparative",
  "section": "Results"
}]

Claim type guidance:

• experimental — derived from the experiment's own measured data; self-evidencing
• external — references domain knowledge, papers, web data, or datasets not in this PR
• methodological — asserts that a methodology choice is appropriate or valid
• comparative — compares to prior work, published results, or other baselines

Subagent prompt template:

> You are extracting factual claims from a section of a GitHub PR diff for a research report. > Section: [{sectionname}] > Scope: examine only the + lines in the diff content provided. > Return a JSON array of claims. Each claim must have: > file, line (new-file line number from the diff), claimtext, claimtype > (one of: experimental, external, methodological, comparative), section. > > Claim type guidance: > - experimental: derived from experiment data in this PR (self-evidencing) > - external: references external knowledge, papers, or datasets not in this PR > - methodological: asserts a methodology choice is appropriate or valid > - comparative: compares to prior work, published results, or baselines > > If no claims found in this section, return an empty array []. > Diff content for section [{sectionname}]: > {sectiondiffcontent}

Aggregate all extracted claims from all subagents. Save to {{AUTOSKILLIT_TEMP}}/audit-claims/claims_{pr_number}.json.

Phase 2 — Evidence Matching (parallel subagents by claim type)

Group extracted claims by claim_type. Launch one Task tool subagent (model: "sonnet") per non-empty group. Each subagent receives the claim list and the full PR diff, and returns findings:

[{
  "file": "research/report.md",
  "line": 42,
  "dimension": "external|methodological|comparative",
  "severity": "critical|warning|info",
  "message": "Claim references [Paper X] but no citation appears in the diff",
  "requires_decision": false
}]

Evidence rules per claim type:

• experimental — always self-evidencing; no finding generated (skip this group)
• external — requires a citation [N] or inline reference within the report; absence

of citation is warning; absence for a specific numeric comparison is critical

• methodological — requires a rationale or supporting reference; absence is warning
• comparative — requires attribution; "comparable to state-of-the-art" without citation

is critical

Subagent prompt template:

> You are checking citation evidence for [{claimtype}] claims in a GitHub PR diff. > For each claim, determine whether adequate supporting evidence exists in the diff. > Return a JSON array of findings for claims that lack evidence. Each finding must have: > file, line, severity (critical/warning/info), dimension (the claimtype value), > message, requiresdecision (boolean). > > Set requiresdecision=true ONLY when the correct path forward is genuinely ambiguous > and cannot be determined without human judgment. > Set requiresdecision=false for all cases with a clear fix (add citation, qualify claim, > remove claim). > > Evidence rules for [{claimtype}]: > {evidencerulesfortype} > > If all claims have adequate evidence, return an empty array []. > Claims to check: > {claimsjson} > Full PR diff: > {diff_content}

Save findings to {{AUTOSKILLIT_TEMP}}/audit-claims/findings_{pr_number}.json.

Step 4: Aggregate and Deduplicate Findings

1. Collect all Phase 2 subagent JSON responses
2. Deduplicate by (file, line) pairs — keep highest severity for each pair
3. Bucket by actionability:

• actionable_findings — requires_decision=false AND severity in ("critical", "warning")
• decision_findings — requires_decision=true (any severity)
• info_findings — severity == "info" AND requires_decision=false

Step 4.5: Echo Primary Obligation

After aggregating all subagent findings, before proceeding to verdict or posting, you MUST state aloud:

> "I have N findings. My primary job is to post inline comments on specific code lines for each finding. I must use the GitHub Reviews API to leave comments anchored to the exact lines in the diff."

This is not optional. Do not proceed to Step 5 without stating this.

Step 5: Determine Verdict

decision_findings = [f for f in all_findings if f.get("requires_decision")]
actionable_findings = [
    f for f in all_findings
    if not f.get("requires_decision") and f["severity"] in ("critical", "warning")
]

if actionable_findings:
    verdict = "changes_requested"
elif decision_findings:
    verdict = "needs_human"
else:
    verdict = "approved"

Step 6: Post Inline Review Comments

Build review comment bodies for each critical and warning finding. Use the line and side fields (modern GitHub Reviews API — not the deprecated position field).

COMMENTS_JSON=$(jq -n --argjson findings "$FINDINGS" '
  $findings
  | map(select(.line != null and (.line | type) == "number" and .line > 0))
  | map({
    path: .file,
    line: .line,
    side: "RIGHT",
    body: ("[" + .severity + "] " + .dimension + ": " + .message)
  })
')

jq -n \
  --arg body "AutoSkillit Citation Audit — Verdict: {verdict}" \
  --arg event "{APPROVE|COMMENT|REQUEST_CHANGES}" \
  --argjson comments "$COMMENTS_JSON" \
  '{body: $body, event: $event, comments: $comments}' | \
gh api /repos/{owner}/{repo}/pulls/{pr_number}/reviews \
  --method POST --input -

Event mapping:

• approved → APPROVE
• needs_human → COMMENT
• changes_requested → REQUEST_CHANGES

Fallback Tier 1 — Individual Comments (if batch POST fails):

Track success and failure counts across all individual post attempts:

COMMIT_ID=$(gh pr view {pr_number} --json headRefOid -q .headRefOid)
tier1_success=0
tier1_failed=0

# For each finding:
if gh api /repos/{owner}/{repo}/pulls/{pr_number}/comments \
  --method POST \
  --field path="{finding.file}" \
  --field line={finding.line} \
  --field side="RIGHT" \
  --field commit_id="$COMMIT_ID" \
  --field body="[{finding.severity}] {finding.dimension}: {finding.message}"; then
  tier1_success=$((tier1_success + 1))
else
  tier1_failed=$((tier1_failed + 1))
  echo "Warning: failed to post individual comment for {finding.file}:{finding.line}" >&2
fi

echo "Fallback Tier 1: $tier1_success succeeded, $tier1_failed failed"

Proceed to Fallback Tier 2 only if tier1_success == 0 (all individual posts failed). If at least one post succeeded, skip Tier 2.

Fallback Tier 2 — DEGRADED: Bullet-List Summary Dump (if all individual posts fail):

Before posting, state:

> "FALLBACK: I was unable to post inline comments. Posting summary as review body instead. This is a DEGRADED review."

gh pr review {pr_number} --comment --body "{summary_markdown}"

Step 6.5: Post-Completion Confirmation

After completing Step 6, you MUST state:

> "I confirm that I posted N inline comments on the following files: [list files]. If I posted 0 inline comments and had findings, this review has FAILED its primary purpose."

Step 7: Submit Summary Review

# approved
gh pr review {pr_number} --approve --body "AutoSkillit citation audit passed. No unsupported claims found."

# changes_requested
gh pr review {pr_number} --request-changes --body "AutoSkillit citation audit found {N} claims lacking evidence. See inline comments."

# needs_human
gh pr review {pr_number} --comment --body "AutoSkillit citation audit: uncertain citation requirements detected. Please review. See inline comments."

Step 8: Write Summary and Emit Verdict

Save findings summary to {{AUTOSKILLIT_TEMP}}/audit-claims/summary_{pr_number}_{timestamp}.md.

Output the verdict as the final line:

> IMPORTANT: Emit the structured output tokens as literal plain text with no > markdown formatting on the token names. Do not wrap token names in **bold**, > *italic*, or any other markdown. The adjudicator performs a regex match on the > exact token name — decorators cause match failure.

verdict = {approved|changes_requested|needs_human}

Exit 0 in all normal cases (approved, needshuman, changesrequested). Exit 1 only for unrecoverable tool-level errors.

Temp File Layout

{{AUTOSKILLIT_TEMP}}/audit-claims/
├── diff_{pr_number}.txt
├── claims_{pr_number}.json          (Phase 1 output)
├── findings_{pr_number}.json        (Phase 2 output)
└── summary_{pr_number}_{ts}.md

Output

• verdict=approved — No unsupported claims; citation integrity is clear
• verdict=changes_requested — Missing citations or unsupported claims found; recipe routes to resolve step
• verdict=needs_human — Ambiguous citation requirements; human review requested

Summary written to: {{AUTOSKILLIT_TEMP}}/audit-claims/summary_{pr_number}_{timestamp}.md

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: TalonT-Org
• Source: TalonT-Org/AutoSkillit
• License: MIT

Install and usage instructions live in the source repository linked above.