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Api For Yourself

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mohitagw15856
api-for-yourself

Publish 'how to work with me' as a literal API spec — endpoints (what to ask me for and what you'll get back), rate limits (meeting and interrupt tolerance), error codes (what happens when you surprise me Friday 5pm), auth (how to earn trust), and a changelog. Use when onboarding to a new team, when a new manager or report arrives, for a team working-styles session, or 'write my README/user manual'. Produces a personal API spec that's genuinely funny and secretly the best onboarding doc on the team.

Overview

Publishermohitagw15856
Repositorypm-claude-skills
Skill nameapi-for-yourself
Stars
1.4K
Forks
240
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by mohitagw15856 on GitHub. Read the source before you install it.

Installation

Install the Api For Yourself AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git /tmp/pm-claude-skills
mkdir -p .claude/skills
cp -r /tmp/pm-claude-skills/exports/openclaw/api-for-yourself .claude/skills/api-for-yourself
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api For Yourself in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Api For Yourself on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Api For Yourself is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

API For Yourself Skill

"User manual for me" documents have existed for years and mostly read like horoscopes ("I value transparency"). The API-spec format fixes them by force: an endpoint must say what you send and what comes back; a rate limit must be a number; an error code must name the actual failure behaviour. The joke is the format — the payload is real self-knowledge, and the test of every line is would a new teammate behave differently after reading it? Deadpan technical voice, honest contents, one page.

What This Skill Produces

  • A personal API spec: endpoints, request formats, rate limits, error codes, auth & scopes, dependencies, scheduled maintenance, changelog — in deadpan OpenAPI-ish style
  • A quickstart at the top: the three calls that cover 90% of integrations with this human
  • Optionally a team version: specs for a whole team session, plus the facilitation note for running it as an exercise

Required Inputs

Ask for (if not already provided):

  • How people should bring them things: channel preferences, context depth (one-liner or brief?), and what makes a request instantly workable vs instantly annoying
  • Real capacity: meeting tolerance per day, focus blocks, response-time honest averages by channel
  • Actual failure modes, told honestly: what happens when they're surprised late Friday, overloaded, given vague asks, or micromanaged
  • What earns trust and what burns it; energy sources and drains; current quirks a teammate would discover in week three anyway

Process

  1. Interview past the horoscope. For every generic answer ("I like directness"), push for the behavioural version: what does a well-formed request actually contain? What's the observable symptom when it's missing? The spec is built from behaviours, not values.
  2. Design the endpoints — the 4–6 things people actually come to this person for. Each gets: method + path (POST /decisions), request body (what to include), response (what they'll get and by when), and the errors it can throw. Include one honest deprecated endpoint (/status-meetings — deprecated, use async /updates instead).
  3. Publish real numbers. Rate limits with actual figures ("3 meetings/day before response quality degrades — 429 after that"), response-time SLAs by channel that match reality, scheduled maintenance (focus blocks, the school run, timezone). A limit without a number is a mood.
  4. Write error codes as self-knowledge. The funniest section and the most useful: 429 Too Many Meetings (symptom: monosyllabic replies; retry: tomorrow morning) · 400 Vague Request (returns clarifying questions, not work) · 503 Friday 5pm Surprise (accepted but not processed until Monday; don't resend). Each code: symptom, what NOT to do, the retry strategy.
  5. Auth, changelog, quickstart. Auth: how trust levels are earned and what each unlocks (scope: direct-feedback granted after…). Changelog: 2–3 honest entries ("v3.1: no longer needs to win every argument — patched after 2024 retro"). Quickstart on top: the three most-used calls, copy-paste ready.

Output Format

# [Name] API — v[X.Y]
> One-line summary of what this human is for.

## Quickstart
[The 3 calls covering 90% of use]

## Endpoints
### POST /[thing]
Request: … · Response (SLA): … · Errors: [codes]

## Rate limits
[Real numbers: meetings, interrupts, context switches]

## Error codes
| Code | Trigger | Symptom you'll observe | Retry strategy |

## Auth & scopes
[How trust is earned; what each level unlocks]

## Scheduled maintenance
[Focus blocks, hours, timezone truths]

## Changelog
[2-3 honest entries — growth as version notes]

Quality Checks

  • Every line passes the behaviour test: a new teammate would act differently having read it — zero horoscope lines survive
  • Rate limits and SLAs carry real numbers the person will actually honour
  • At least one error code and one changelog entry required genuine honesty (a flaw admitted, a patch noted) — that's what makes readers trust the rest
  • The joke never outruns the information: deadpan format, true payload
  • One page; the quickstart works standalone if that's all anyone reads

Anti-Patterns

  • Do not write requirements-for-others disguised as self-documentation — it's an API you offer, not an SLA you impose; tone stays "here's how to get the best out of me"
  • Do not fake quirks for comedy or hide real ones for image — week three reveals everything anyway
  • Do not ship without the errors section; specs with only happy paths are marketing
  • Do not let it ossify — the changelog implies maintenance; suggest a re-version at role changes

Related

[[the-understudy]] is how an AI learns your inside; this is how humans call your outside. [[working-agreements]] for the team-level contract; [[onboarding-plan]] to slot this into a new joiner's week one.

Frequently asked questions

What does the Api For Yourself AI skill do?

Publish 'how to work with me' as a literal API spec — endpoints (what to ask me for and what you'll get back), rate limits (meeting and interrupt tolerance), error codes (what happens when you surprise me Friday 5pm), auth (how to earn trust), and a changelog. Use when onboarding to a new team, when a new manager or report arrives, for a team working-styles session, or 'write my README/user manual'. Produces a personal API spec that's genuinely funny and secretly the best onboarding doc on the team.

Why use Api For Yourself on TypingMind?

Because you install it once and use it with any model. Api For Yourself is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Api For Yourself in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mohitagw15856/pm-claude-skills/tree/main/exports/openclaw/api-for-yourself. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Api For Yourself?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Api For Yourself?

As many as you like. As long as a model supports skills, you can use Api For Yourself with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Api For Yourself AI skill free?

Yes. It is published on GitHub by mohitagw15856 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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