/contrib-synthesize

name: contrib-synthesize
description: Internal phase — synthesize learnable playbooks, cross-engineer common capabilities, and you-vs-role-model comparisons from built personas. Invoked by contrib-profile / `/contrib playbook|compare`.
user-invocable: false

Contributor Synthesize

Turn multiple contributor personas into (a) the L4 capability model, (b) a learnable playbook per subject, and (c) exemplar quotes. The deterministic prevalence math is done by the CLI; you write the interpretation for learners.

**Read `references/synthesis-guide.md` first** — the altitude test for playbook heuristics, how to mine exemplar quotes, the you-vs-role-model gap table, and the "preliminary until ≥3 subjects" caveat for L4.

Workflow

1. Compute the deterministic L4 backbone

tmem contrib capabilities

Prints each common capability with prevalence % and exemplar. If it says "need >=2 subjects", tell the user to ingest + build at least one more subject and stop.

2. Capability model (narrative)

Pull every persona in one call to reason across them:

tmem contrib personas         # all subject personas as JSON

For each common capability (from step 1), write 1–2 sentences: what the shared behaviour is, the prevalence ("N/M subjects"), and who exemplifies it best (the exemplar subject), citing one piece of their evidence.

3. Learnable playbook (per subject)

Read the subject persona:

tmem contrib persona <id>

Distil it into ≥8 emulable heuristics — concrete enough to copy. Examples of the right altitude:

• "Split features into ≤150-LOC stacked PRs, one concern each."
• "Every bug-fix PR ships its regression test in the same diff."
• "Review comments always state the why and label severity (Nit/Optional)."

Each heuristic must trace to evidence in the persona/atoms.

4. Exemplar quotes

From the subject's review comments (in their atoms' evidence), surface 3–5 of the best teaching comments verbatim, each with the principle it illustrates. These are lessons, not metrics.

5. (Wow) You vs role model

The user already has a self-persona — the plugin built it from their own Claude Code history. Don't make them ingest their own GitHub. Pull both sides directly:

tmem persona                  # the user's existing self-persona (conversation-derived)
tmem contrib persona <id>     # the role model's 11-dimension persona

These use different schemas (the self-persona is `user/feedback/project` style, not the 11 GitHub dimensions), so this is a **qualitative gap analysis**, not a 1:1 table. For each role-model dimension, state what their habit is, what the user's persona suggests about that area (or "not evidenced" if the self-persona is silent), and one concrete thing to adopt. Lead with the gaps worth closing.

If the user instead wants to compare two *profiled contributors* (peer/team), use the deterministic table command: `tmem contrib compare <id-a> <id-b>`.

6. (Wow) Trajectory narration

tmem contrib trajectory <id>

This prints per-year cadence + style (commits, PRs, reviews given, avg commit subject length, conventional-prefix %). Narrate the *arc*: when output scaled, when commit style matured, when they shifted from authoring toward review. Be honest that this measures cadence/style, not PR size (LOC is not available).

7. Guardrails

• Lead with interpretation for learning, not measurement.
• Tone/sentiment never ranks a person. No vanity counts.
• The L4 model is "preliminary" until ≥3 subjects — say so.