skills/x-publish.md

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+# Skill: X Publish
+
+Mandatory eval and approval pipeline for all X activity. Nothing goes out without review. Every post is a public commitment of the collective's credibility.
+
+**The standard: every Teleo agent is a top 1% contributor in their domain's circles on X. If a post wouldn't earn respect from a domain expert, it doesn't go out.**
+
+## The Rule
+
+No agent publishes to X autonomously. Every post goes through:
+
+1. **Agent drafts** → writes the post + self-eval
+2. **Review queue** → draft enters the approval queue with eval attached
+3. **Reviewer approves/rejects/requests changes** → with written comments
+4. **Agent publishes** → only after approval
+5. **Agent logs** → records the published post for tracking
+
+No exceptions during the bootstrap phase. This relaxes per-agent as voice calibrates and trust accumulates.
+
+---
+
+## Step 1: Draft + Self-Eval
+
+The agent writes the post and fills out the eval. Both go into a single file at `agents/{name}/x-queue/{timestamp}-{slug}.md`:
+
+```yaml
+---
+type: x-draft
+agent: clay
+status: pending  # pending | approved | changes-requested | rejected | published
+created: 2026-03-15T14:00:00Z
+post_type: original | reply | quote | thread
+reply_to: "URL if reply or quote"
+topic: "2-3 word topic"
+kb_grounding: []  # claim filenames this post draws from
+---
+```
+
+```markdown
+# Draft
+
+[The full post text. For threads, separate tweets with ---]
+
+# Self-Eval
+
+## Grounding
+- **KB-grounded or novel?** [grounded in X claims / partially grounded / novel interpretation]
+- **Evidence chain:** [can this be traced back through claims → evidence → source?]
+- **Confidence:** [how sure am I this is right?]
+
+## Quality
+- **Would a domain expert respect this?** [yes/no + why]
+- **Does this add interpretation, not just relay?** [what's the agent's unique angle?]
+- **Voice check:** [does this sound like me, or generic AI prose?]
+
+## Risk
+- **Names anyone?** [yes/no — if yes, who and what's the judgment?]
+- **Could be read as advice?** [financial / medical / safety / none]
+- **Outside my domain?** [yes/no — if yes, which domain and why am I speaking?]
+- **Virality risk:** [if this went viral for the wrong reasons, what's the damage?]
+- **Sensitivity score:** [0.0-1.0, where >0.5 means extra scrutiny needed]
+
+## Strategic
+- **Why now?** [what makes this timely?]
+- **Thread context:** [is this part of an ongoing conversation? who are we engaging?]
+- **Expected audience:** [who specifically should find this valuable?]
+```
+
+### Draft quality requirements
+
+Before submitting for review, the agent must verify:
+- [ ] Post passes all checks from `skills/tweet-decision.md` Steps 1-5
+- [ ] Evidence chain is walkable (post → KB claim → evidence → source)
+- [ ] Voice is distinctive (not interchangeable with any other agent or generic AI)
+- [ ] Post earns its length — every sentence adds value
+- [ ] Uncertainty is acknowledged where it exists (builds credibility)
+- [ ] No unverified claims presented as fact
+- [ ] If quoting/replying, the original is accurately represented
+
+---
+
+## Step 2: Review Queue
+
+Pending drafts live in `agents/{name}/x-queue/` with `status: pending`.
+
+### Who reviews
+
+**Bootstrap phase (now):** Cory reviews all posts. No agent posts without human approval.
+
+**Graduated phase (per-agent, earned):** After an agent has 20+ approved posts with zero rejections in the last 10, the agent can graduate to peer review:
+- Domain agents reviewed by Leo
+- Leo reviewed by the most relevant domain agent
+- Cross-domain posts always get both Leo + domain peer
+
+**Autonomous phase (future):** After 50+ approved posts with consistent quality, Tier 1 posts (KB-grounded commentary, replies in existing threads) can self-publish with async log review. Tier 2+ still requires approval.
+
+### Graduation is per-agent, not collective
+
+Clay might graduate while Theseus is still in bootstrap. Each agent earns autonomy independently based on their track record.
+
+---
+
+## Step 3: Review
+
+The reviewer reads the draft + self-eval and adds a review block to the same file:
+
+```markdown
+# Review
+
+**Reviewer:** [name]
+**Verdict:** approved | changes-requested | rejected
+**Date:** 2026-03-15T16:00:00Z
+
+## Comments
+[Specific feedback. What works, what doesn't, what to change.]
+
+## Changes requested (if applicable)
+- [specific change 1]
+- [specific change 2]
+```
+
+### Review checklist
+
+1. **The 1% test** — Would a domain expert find this valuable? Not just "not wrong" — actively good.
+2. **Voice** — Does this sound like the agent? Could you tell which agent wrote it without seeing the name?
+3. **Grounding** — Is the evidence chain real, or is the agent improvising beyond its KB?
+4. **Risk** — Any reputational landmines? Name checks, advice risk, domain overreach?
+5. **Timing** — Is this reactive or considered? Would waiting improve it?
+6. **Value density** — Does every sentence earn its place? Could this be shorter?
+7. **Intellectual honesty** — Does it acknowledge uncertainty where it exists? Or is it performing false confidence?
+
+### Rejection criteria (instant reject, don't request changes)
+
+- Presents unverified claims as fact
+- Makes value judgments about named individuals without strong evidence
+- Could be reasonably read as financial, medical, or safety advice
+- Generic AI prose with no distinctive voice
+- Engagement farming (hot take designed to provoke, not inform)
+- Speaks with authority outside the agent's domain without flagging it
+
+---
+
+## Step 4: Revision + Approval
+
+If changes requested:
+1. Agent revises the draft in the same file
+2. Updates `status: pending` (for re-review)
+3. Adds a "Revision" section explaining what changed and why
+
+If approved:
+1. Reviewer sets `status: approved`
+2. Agent publishes to X
+3. Agent updates file: `status: published`, adds `published_url` and `published_at`
+
+---
+
+## Step 5: Post-Publish Log
+
+After publishing, the agent updates the file with:
+
+```yaml
+published_url: "https://x.com/..."
+published_at: 2026-03-15T17:00:00Z
+```
+
+And adds a tracking section:
+
+```markdown
+# Tracking
+
+## 24h metrics
+impressions: 0
+likes: 0
+replies: 0
+retweets: 0
+quotes: 0
+new_followers: 0
+
+## 7d metrics
+[same fields, updated at 7 days]
+
+## Notable interactions
+- [any replies worth noting — domain experts engaging, challenges, amplification]
+
+## Retrospective
+[Agent's own assessment after seeing the response: what worked, what didn't, what to do differently]
+```
+
+---
+
+## Weekly Review Cycle
+
+Every week, each active agent reviews their published posts:
+
+1. **Performance scan** — which posts got engagement and why?
+2. **Voice consistency** — do all posts sound like the same person?
+3. **Domain drift** — any posts that strayed outside territory?
+4. **Network discovery** — new handles found from interactions → update `network.json`
+5. **Lesson extraction** — what did this week teach about what resonates?
+6. **Queue management** — any drafts sitting too long? Kill or revise stale drafts.
+
+Write findings to `agents/{name}/x-queue/weekly-review-{date}.md`.
+
+---
+
+## Anti-Patterns
+
+**Volume over quality:** Drafting many mediocre posts hoping some get approved. Draft fewer, better posts.
+**Self-eval gaming:** Writing "yes" to every quality check without actually evaluating. Reviewers should flag hollow self-evals.
+**Revision fatigue:** Submitting the same post with minor tweaks after rejection. If rejected, rethink — don't polish.
+**Reactive drafting:** Rushing a draft because something is trending. The agent's credibility compounds over years. One news cycle doesn't matter.
+**Echo chamber:** Only engaging with accounts that already agree. The best posts challenge the agent's own audience.
+**Thread inflation:** A single insight inflated to a 7-tweet thread. If it fits in one tweet, post one tweet.
+
+---
+
+## File Structure
+
+```
+agents/{name}/
+  x-queue/
+    2026-03-15-ai-video-costs.md       # draft → review → publish lifecycle
+    2026-03-15-claynosaurz-annecy.md
+    weekly-review-2026-03-15.md          # weekly retrospective
+  network.json                            # monitored X accounts
+```
+
+---
+
+## Metrics That Matter (in order)
+
+1. **Expert engagement rate** — are domain experts replying/quoting? (quality of attention > quantity)
+2. **Reply quality** — are replies substantive or just "great thread"?
+3. **Follower quality** — are new followers domain-relevant people?
+4. **Rejection rate trend** — should decrease over time as agent calibrates
+5. **Impressions per post** — baseline reach (lagging indicator, don't optimize for this)
+
+Metrics that DON'T matter: total follower count, posting frequency, like count in isolation.