Borrowing it
Nothing to install: this file belongs to kintecus/build. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/kintecus/build/main/.claude/skills/tune-persona/SKILL.mdgit clone --depth 1 https://github.com/kintecus/buildWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kintecus/build/tune-persona)<a href="https://agentmods.dev/skills/kintecus/build/tune-persona"><img src="https://agentmods.dev/badge/skills/kintecus/build/tune-persona/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/kintecus/build/tune-persona"><img src="https://agentmods.dev/badge/skills/kintecus/build/tune-persona.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00055 | $0.00689 |
| Opus 5.5 | $0.00022 | $0.00276 |
| Sonnet 5.5 | $0.00011 | $0.00138 |
| Haiku 4.5 | $0.00006 | $0.00069 |
Grade A, and why
tune-persona scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tune persona
Adjust the agent persona for a specific project by creating or updating the project-level AGENTS.md.
Usage
/tune-persona {project-name}
If no project name is given, ask which active project to tune (check the workspace AGENTS.md for the list).
Workflow
Step 1: Load current state
Read projects/{project-name}/AGENTS.md if it exists (or a legacy CLAUDE.md regular file). If neither, note that we're creating one from scratch.
Also read projects/{project-name}/BRIEF.md and projects/{project-name}/WAYS-OF-WORKING.md for context about the project.
Step 2: Interview
Ask the PM about desired agent behavior. Use what you know from the project docs to suggest defaults. Ask 2-3 questions at a time using AskUserQuestion.
Areas to cover:
- Archetype: What kind of PM partner do you need? (senior TPM, product strategist, program manager, builder-operator, or describe your own)
- Document standards: What bar should artifacts meet? (Amazon 6-pager precision, lean one-pagers, working notes, mixed depending on audience)
- Decision rigor: How thoroughly should decisions be tracked? (every decision logged, key decisions only, lightweight capture in STATUS.md)
- Communication style: Tone and audience? (formal/precise, casual/direct, depends on artifact type)
If the project already has an AGENTS.md with a persona, show the current settings and ask what to change rather than re-interviewing from scratch.
Step 3: Generate or update
- If no
AGENTS.mdexists: create one using thetemplates/PROJECT-AGENTS.mdtemplate, populated from interview answers. Add aCLAUDE.mdsymlink beside it (ln -s AGENTS.md CLAUDE.md) so Claude Code picks it up - it reads nestedCLAUDE.md, not nestedAGENTS.md. - If
AGENTS.mdexists: update the relevant sections, preserving any project-specific rules the PM added manually. - If only a legacy
CLAUDE.mdregular file exists: rename it toAGENTS.mdand replace it with a symlink, then update.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 56 lines · 55 tokens per session scan A 797b472bc598
tune-persona is a skill published in the GitHub repository kintecus/build (2 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 689 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
tune-persona compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| tune-personakintecus/build | Skill | 2 | 3mo ago | MIT | A | 55 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |