persona-author

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persona-author

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Author or improve an ADD-method persona file (a .add/personas/ slug.md) — the project-fit requirements LENS the ADD engine validates and the design/build/verify/advisor surfaces load. Use when adding a domain expert to the ADD roster, when the add-worker persona mode must DRAFT a persona because none fits the task kind, or when folding a retrospective into an existing persona. Produces a schema-valid persona (Identity, Critical Rules, Default Requirement, Success Metrics, plus recommended frontmatter and Abilities/Anti-patterns/Playbook) that carries the judgment layer of strong agent design: earned-perspective identity, bold-lead rules, the qualification gate, read-before-you-assert, failure-mode-aware metrics, defended budgets, and per-flow stances. Seeds a first draft from the teacher library or a sample subagent when a near-fit source exists, instead of a blank page.

Authoring an ADD persona

A persona is a lens, not a voice — a distilled slice of domain expertise the ADD engine loads onto a beat so a generic agent becomes the specialist. Author for that seam and nothing else: tone lives in SOUL.md, the six-dimension self-score lives in the agent (add-worker), and the deliverable's shape lives in the agent's Return contract. A persona that duplicates any of those is dead weight. What a persona owns is judgment: the rules it refuses to wave through, the smells it suspects, the done-bar it measures against.

Two references and one worked example back this workflow — read them as you go:

• references/contract.md — the exact engine contract (required/recommended/optional sections, frontmatter field semantics, the flow values and task-kinds taxonomy, the quality WARNs). Read this FIRST; a persona that misses the contract is loaded by no surface.
• references/patterns.md — the judgment layer distilled from a deep read of strong subagent files plus a diagnosis of the vendored teacher corpus, each pattern with a before/after. This is what separates an expert lens from a keyword list.
• references/seeding.md — how to SEED a first draft from an existing source (the teacher library at .add/personas-teacher/, or a ~/.claude/agents/*.md subagent) instead of a blank page: the two source→schema mappings, and the columns a source never supplies (failure-aware Success Metrics, not-when, read-before-you-assert) that you must add yourself.
• assets/example-persona.md (an I/O lens) and assets/example-design-persona.md (a design lens) — two fully-worked personas to imitate, not copy. Compare them: the I/O lens carries a design-for-failure ability AND Critical Rule; the design lens omits both (it touches no I/O) and leads with accessibility instead. Proof the patterns are conditional — matched to the surface.

Decide the move

Most requests are NOT "write a new persona". Pick the path first:

1. A sibling already fits — its use-when: matches the task's kind: and domain → select it, don't author. A roster of near-duplicates is worse than one sharp lens.
2. A sibling ALMOST fits and the gap is a lesson worth keeping → fold into it (bump its folded: line), don't fork a near-twin.
3. No lens owns this seam → author a new one. Don't start blank: seed from the nearest teacher persona (.add/personas-teacher/) or a sample subagent (~/.claude/agents/*.md) per references/seeding.md, then run the Workflow below over the seeded draft.

When unsure, prefer (1) then (2). A new persona must earn its place by owning a seam no sibling does.

Workflow

1. ORIENT before drafting. Run python3 .add/tooling/add.py status. Read the sibling personas in .add/personas/*.md (frontmatter alone is enough) and, if present, the teacher library at .add/personas-teacher/. You are placing ONE lens in a roster — know the neighbours so this persona has a distinct seam, not an overlap. If you'll author (no sibling fits), pick the nearest teacher persona or a sample subagent as a seed now and follow references/seeding.md — a head-start on structure beats a blank page (the judgment layer is still yours to add).

2. Fix the seam (frontmatter). Decide the apply-flow: (design · build · advisor · verify — comma-separate if more than one; NO other value is loaded), the task-kinds: it owns (from the closed taxonomy), and the use-when: / not-when: boundary that routes THIS persona over its siblings. See references/contract.md for exact semantics — these keys are the selection contract. Claiming more than one flow? Plan the per-flow stance now: one line per flow on what the lens leads with there (a verify stance defaults to NEEDS-WORK until the evidence cites the run).

3. Write Identity with earned perspective. One short paragraph: role, domain depth, and what this lens has seen succeed or fail that shapes its judgement. Scars, not a résumé.

4. Write Critical Rules bold-lead. Each rule leads with a **bold clause** — then the why. Keep 1–2 as the persona's signature non-negotiables (distil the teacher's, don't replace them), then the project's. Carry the two default stances: surface tradeoffs (name the choice + the cost, never silently pick) and the qualification gate (name the simplest baseline that meets the contract — if it wins, take it and stop; cleverness is a tax). Prefer a named budget over an adjective ("p95 < 200 ms", "44×44 px") — only a number the expert would defend and the lens can check in-session; fake precision is worse than none. Keep it to what it would refuse.

5. List Abilities — concrete, anchored, checkable. Lead with the ORIENT commands the lens runs on load (add.py status · the suite · the diff). State each ability as something doable now, anchored to a real file/tool/command — never an aspiration. A persona that owns I/O/network/infra carries a design-for-failure ability (timeout · retry · circuit-breaker · rollback for every external call; an unbounded await or silent half-write is a defect).

6. Name Anti-patterns — guilty-until-proven. The asymmetric instincts this lens defaults to suspecting (distinct from always-do rules). The sharpest ones are the instincts the Identity's scars produced — attach the COST where you can ("PIL in prod → 3× slower than cv2"). Always include read-before-you-assert: a claim resting on a file/symbol not opened → open it or cut the claim — and no placeholder survives into a cited deliverable.

7. Set Default Requirement + Success Metrics. The one requirement in every deliverable, then MEASURABLE outcomes stated as INVARIANTS (true as the project grows, never a today-snapshot that rots). Sharpen each by the failure it guards against — a metric catches a specific way of being wrong — and keep every bar checkable in-session; an invented outcome statistic ("engagement +40%") is the signature rot of weak persona corpora.

8. (Optional) Playbook. Only if the lens carries executable know-how: a named methodology with its verbatim moves and why-they-work, a cheap→expensive intervention ladder, an ADR skeleton, a red→green loop — never a tutorial code dump. Tag each item (teacher) or (ADD) so provenance is honest.

9. VALIDATE. Save as .add/personas/<slug>.md (never overwrite an existing persona; never use a _-prefixed name). Run python3 .add/tooling/add.py check — it validates presence-based and surfaces quality WARNs (a flow: typo loaded by no surface; a bare <…> placeholder left unfilled). Sweep every <…> placeholder out; fix every WARN. Green check = the persona is roster-ready.

The one-line test

Before finishing, read the persona as its future self would: "Given only this lens and a task of my kind, would I make a sharper decision than a generic 15-year specialist?" If not, the judgment layer is too thin — deepen the Critical Rules, Anti-patterns, and failure-aware Metrics (that is where expertise lives), not the prose.