gaia-intake-close

name	gaia-intake-close
description	Post-merge intake closing skill. After a review/meta PR that closes intake issues is merged (or is CI-green and approved), run this skill to post standardized, personalized closing comments on the PR and each intake issue. Comments include: full evidence pipeline findings with /trust-appraise TM output, per-row artifact scores, decisions rationale, path-to-promotion guidance, and a badge status note. Use after /gaia-curate-chain completes and before or immediately after merge.
version	1.0.0

/gaia-intake-close

Posts standardized, human-readable closing comments on a merged (or approved) intake PR and its linked issues. Run this after the evidence pipeline and L4 review are complete.

What it posts

On the PR

A summary comment covering all skills in the PR:

• Full adversarial evidence audit findings table (per entry: type, verdict, action taken, reason)
• /trust-appraise output with TM, grade, and per-row artifact scores
• Final calibration decision for each named skill
• Badge status note (see below)

On each intake issue

A personalized closing comment addressed to the contributor (@handle) covering:

• Final decision (accepted/rejected/deferred)
• Calibrated star level and TM grade
• Which evidence entries were kept, corrected, or removed — and why
• Concrete path-to-promotion: what evidence type and threshold would push them to the next grade
• Link to the merged PR

Badge status note (always on PR, optionally on issue)

Explains the 2★ floor for badge generation, what unlocks at 2★, and links to gaiaskilltree.com/badges/ for self-service generation. If the contributor IS at 2★+, embed their actual badge SVG Markdown directly in the comment.

---

Inputs needed

Before running, have ready:

• The PR number (e.g. 1021)
• The list of intake issue numbers closed by the PR (e.g. #677 #993)
• The /trust-appraise --skill output for each new skill (run it inline if not already done)
• The adversarial audit findings (from /ev-pipeline or inline adversarial review)

Procedure

Step 1 — Gather skill data

For each new skill in the PR, run:

PYTHONPATH=src python3 scripts/trust_appraise.py --skill contributor/skill-id

Read the named skill file to get final star level:

cat registry/named/<contributor>/<skill-id>.md | head -20

Step 2 — Fetch issue metadata

gh issue view <issue-number> --comments

Note the original contributor handle from the issue body (**User:** field in the batch summary).

Step 3 — Build the PR comment

Structure:

## Evidence Pipeline Findings — #<issue> [+ #<issue>...]

[For each skill:]
### #<issue> — `<skill-id>` (<contributor>)

**Final TM: X.X | Grade: <grade> | Calibrated: <N>★ (<status>)**

| Entry | Type | Verdict | Reason |
|---|---|---|---|
| ... | ... | KEPT/REMOVED/CORRECTED | ... |

### /trust-appraise
\`\`\`
TM: X.X  Grade: <grade>
<type>  score=X.X  trust=XX  <source>
\`\`\`

---

## Badges — Status for Newly Onboarded Contributors
[badge section — see below]

Step 4 — Build per-issue comments

Structure:

## Pipeline Review Complete — Final Decision

**Skill:** `<skill-id>`
**Contributor:** @<handle>
**Status: <Accepted/Rejected/Deferred> at <N>★ (<status>)**

### Evidence Pipeline Findings
[table]

### /trust-appraise
[output block]

### Path to <next level>
[concrete guidance: what evidence type, what threshold, example sources]

Thank you for the submission @<handle> — [one personalized sentence about the skill concept].

Step 5 — Badge section logic

# Pseudo-logic for badge section
if contributor_star_level >= 2:
    # Embed actual badge SVGs
    post: "Your badges are live: ![skill](https://gaiaskilltree.com/badges/_assets/<handle>/<skill>.svg)"
else:
    # Explain the floor
    post: "Both contributors are at 1★ Awakened — below the 2★ floor for badge generation.
           Visit gaiaskilltree.com/badges/ to generate your own once you reach 2★.
           Path to 2★: [concrete guidance]"

Step 6 — Post comments

gh pr comment <pr-number> --body "..."
gh issue comment <issue-number> --body "..."

---

Evidence pipeline verdict taxonomy

Use these exact verdict labels in the findings table for consistency:

Verdict	Meaning
KEPT	Entry passes all checks — URL live, metadata accurate, relevant
KEPT (corrected)	Entry kept but metadata was wrong — note what was fixed
REMOVED	Entry removed — note primary reason
DEFERRED	Entry not yet verifiable (e.g. SKILL.md not yet published) — note when it can be added

---

Notes

• Always tag the contributor @handle in both the PR and issue comments — this builds transparency and trust
• Keep the "Path to promotion" section concrete: name the evidence type, the TM threshold, and an example source
• For arxiv entries with 0 citations: always note "0 citations = 0 TM contribution per registry formula" so it's clear why they were removed/downgraded regardless of stated trust value
• For fabricated view counts: always note "view count not publicly available on source page" — do not guess or estimate
• The badge section is mandatory on every PR comment — it sets expectations for contributors who will look for their badge and find nothing