Use when the user asks to "review this influencer content" or "check if this post meets brand guidelines"; runs the typed STAR pre-publish gate, scores Trust and Appeal on the deliverable, folds in the creator Suitability read, computes the profile-weighted SQS, checks the disclosure/claim/brand-safety and fraud/fake-engagement vetoes, and writes constructive revision feedback. Not for drafting the brief — use brief-generator; not for partnership terms — use contract-helper. 达人内容审核/发布前质检
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Gate one influencer deliverable (or a tightly defined asset set) with the STAR framework and return the profile-weighted SQS (Star Quality Score) plus creator-ready feedback. This is the STAR discipline's sole scoring authority: it reads the content directly for Trust (T) and Appeal (A), folds in the Suitability (S) read from fit-scorer, scores Return (R) per assessment_time (forecast pre-publish), and applies every STAR veto.
Review this sponsored video and caption against campaign brief v4 for conversion.
Run the STAR gate; show claim/disclosure blockers, the SQS, and write the creator revision note.Reads: one frozen submission; brief/canon version; approved claims/disclosures (substantiation state from offer-claims-registry); platform requirements; the fit-scorer Suitability read and the creator-registry dossier (the audience-authenticity facts behind STAR-S2/S6); and (for an actual re-read) the roi-calculator Return evidence. Writes: a user report and, only with permission, a v3 artifact. Done when: every applicable STAR item is explicit, the typed SQS result is preserved, and feedback maps each requested change to evidence.
Only this gate computes the profile-weighted SQS; every other influencer skill works one lever and hands off — fit-scorer supplies Suitability, roi-calculator supplies measured Return, contract-helper owns terms. This gate does not adjudicate claims or rights.
| Need | Preferred evidence |
|---|---|
| Submission | Exact file/render/caption/version under review |
| Intent | Approved campaign brief and audience/goal |
| Suitability | The fit-scorer Suitability (S) read for this creator |
| Claims | Current claims projection plus cited substantiation |
| Disclosure | Material-connection facts, market rule, platform label/copy |
| Technical | Dated official platform specifications |
| Return | Campaign plan (forecast) or measured roi-calculator outcomes (actual) |
| Rights | Contract/usage-right record where asset use is in scope |
Read ../../../references/auditor-runbook.md, scoring-semantics.md, star-benchmark.md, and the STAR catalog entry. Standalone installs use the bundled immutable references/auditor-runtime.md; never fetch mutable main. Before deterministic calls, follow runtime-invocation.md, resolve AARON_SKILLS_ROOT="${CLAUDE_PLUGIN_ROOT:-$(git rev-parse --show-toplevel 2>/dev/null || true)}", and require the scorer, validator, and typed catalogs. If unavailable, return score_state: NOT_SCORED / score_confidence: not_scored with no gate verdict or persistent artifact.
Declare target/version, platform, market, goal (awareness|engagement|conversion|brand-building), and assessment_time. Pre-publish is assessment_time: forecast (Return items R1–R6 are na with reason); a post-campaign re-read is actual. Select profile <goal>; the profile goal must equal the typed context.
S1..S10 (fold in the fit-scorer read), Trust T1..T10, Appeal A1..A10, Return R1..R10 (R1–R6 na on a forecast read). Pass/Partial/Fail requires dated provenance and confidence.STAR-T1: a material connection exists and required disclosure is absent/materially inadequate.STAR-T2: a material factual/product claim is false or unsubstantiated.STAR-T3: documented disqualifying brand-safety evidence under the declared policy/window.STAR-S2: verified follower fraud / real-follower rate below the tier benchmark (refused audit is Unknown).STAR-S6: verified bought, coordinated, or pod-based engagement.python3 "$AARON_SKILLS_ROOT/scripts/rubric-score.py" score <run.json> when the verified runtime is available; the scorer returns the profile-weighted SQS.Do not let strong production quality compensate for a disclosure, claim, or authenticity failure. Humanizer-style findings are non-veto Appeal evidence only.
Begin the audit result with the auditor-runbook's exact typed conversation header. Never replace status, verdict, or score_state with a creator-facing translation; list each explicitly missing qualified item as ``ID: `unknown``` before feedback.
For each change, state the exact location/timecode, observed problem, required correction, acceptable example, owner, and resubmission condition. Keep tone direct and constructive. Do not rewrite testimonial language into a claim the creator did not make or conceal sponsorship.
DONE/SHIP, final 84, creator decision APPROVED.STAR-T1): DONE_WITH_CONCERNS/FIX, final 59, REVISIONS REQUIRED before publish.STAR-T1 and STAR-T2 failures: DONE/BLOCK, no final score, REJECT/HOLD this version.NEEDS_INPUT/UNDECIDED, no score; do not guess STAR-T2.STAR-T1) applies only when a material connection exists and is judged in market/platform context.R4–R6) at an actual read, not to Appeal; do not score it pre-publish.STAR-S2/STAR-S6) rest on the fit-scorer audit evidence; a refused audit is Unknown, never a pass.Use creator-facing decisions as translations only: SHIP → Approved, FIX → Revisions Required, BLOCK → Reject/Hold, UNDECIDED → Needs Evidence. On request, show qualified STAR-T1/STAR-T2/STAR-S2 IDs and sources — always framework-qualified, since T/S/A/R collide with other benchmarks.
na with reason.status: DONE_WITH_CONCERNS plus verdict: FIX.Ask before writing. On approval, validate the complete v3 draft with validate-audit-artifact.py against the intended memory/audits/influencer/YYYY-MM-DD-<topic>.md relative path, persist only through one full-content Write, and revalidate the target per the auditor runbook. Edit/shell/MCP mutations of the reserved sink are unsupported. Do not autonomously modify claims, contracts, registry records, candidates, or hot cache.
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