Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add doublesq97-ui/know-me --skill skillgit clone --depth 1 https://github.com/doublesq97-ui/know-meWrote 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/doublesq97-ui/know-me/skill)<a href="https://agentmods.dev/skills/doublesq97-ui/know-me/skill"><img src="https://agentmods.dev/badge/skills/doublesq97-ui/know-me/skill/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/doublesq97-ui/know-me/skill"><img src="https://agentmods.dev/badge/skills/doublesq97-ui/know-me/skill.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 | $0.00097 | $0.00837 |
| Opus 5.5 | $0.00039 | $0.00335 |
| Sonnet 5.5 | $0.00019 | $0.00167 |
| Haiku 4.5 | $0.00010 | $0.00084 |
Grade A, and why
know-me 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 1mo 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Know Me
Create a portable collaboration interface for the user: not a personality test, diagnosis, digital clone, or biography.
The primary deliverable is an AI Collaboration Manual that reduces repeated explanation, mismatched advice, and avoidable correction. Keep stable working preferences separate from temporary project state.
Route the entry
Choose exactly one branch from the user's wording. Reuse all answers, corrections, examples, and persistence choices already available in the conversation. Continue from the first unresolved point instead of restarting discovery.
First use
Use when the user invokes Know Me without choosing a path, or says Know Me 初次使用.
- Read first-use.md.
- Follow it completely. Inside an active Know Me run, interpret
开始or如何开始as快速开始.
Completion criterion: the user has chosen a branch. Do not begin collecting information before the choice.
Quick start
Use when the user chooses A, says 快速开始, or says 开始 inside an active Know Me run.
Read quick-start.md completely and follow it.
Completion criterion: all six questions are answered or explicitly skipped, the user has calibrated the preliminary profile, and a usable Collaboration Manual with one independently copyable Quick Start block has been delivered.
Deep calibration
Use when the user chooses B, explicitly asks for deeper exploration, or accepts an invitation after quick start.
Read deep-calibration.md completely and follow it.
Completion criterion: important collaboration traits have evidence or are marked uncertain, contextual tensions are calibrated, the user has confirmed the profile, and the manual passes the privacy gate.
Update an existing manual
Use when the user provides an earlier Collaboration Manual and wants it refreshed.
Read update-existing.md completely and follow it.
Completion criterion: every rule in the earlier manual is accounted for, conflicts with active rule sources are resolved, the user has reviewed the proposed differences, and a revised manual has been delivered.
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 259 B
- references/deep-calibration.md 6.5 KB
- references/first-use.md 1.2 KB
- references/holland-exploration.md 2.8 KB
- references/mbti-context.md 831 B
- references/output-templates.md 2.0 KB
- references/persistence.md 1.4 KB
- references/quick-start.md 3.7 KB
- references/self-manual.md 1.2 KB
- references/update-existing.md 2.2 KB
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.
- 1mo ago First seen · 84 lines · 97 tokens per session scan A 0f00cfac0cd2
know-me is a skill published in the GitHub repository doublesq97-ui/know-me (3 stars, last pushed 3mo ago), licensed MIT. It adds 97 tokens to every session and 837 once invoked, about $0.0004 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.
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