Borrowing it
Nothing to install: this file belongs to Smart-AI-Memory/attune-ai. 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/Smart-AI-Memory/attune-ai/main/.agents/skills/coach/SKILL.mdgit clone --depth 1 https://github.com/Smart-AI-Memory/attune-aiWrote 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/smart-ai-memory/attune-ai/coach)<a href="https://agentmods.dev/skills/smart-ai-memory/attune-ai/coach"><img src="https://agentmods.dev/badge/skills/smart-ai-memory/attune-ai/coach.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00046 | $0.01223 |
| Opus 5 | $0.00023 | $0.00611 |
| Sonnet 5 | $0.00009 | $0.00245 |
| Haiku 4.5 | $0.00005 | $0.00122 |
Grade A, and why
coach 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 8d 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Coach
IMPORTANT: Start your response by telling the user:
Coach — Explains any Attune topic with progressive depth — concept, then how-to, then full reference.
How It Works
Each depth level serves a different type of content, not just more of the same:
| Level | Type | What you get |
|---|---|---|
| 0 | Concept | What is it? When to use it? |
| 1 | Procedural | Step-by-step: how to run it |
| 2 | Reference | Full detail, edge cases, links |
Repeated calls on the same topic auto-advance. A new topic resets to concept.
Commands
Topic Lookup (default)
If the user provided a topic, call:
help_lookup(topic="<topic>", mode="progressive")
Use the bare topic slug — the engine resolves the right template type at each level:
| User says | Topic slug |
|---|---|
| security audit | security-audit |
| code review | code-review |
| code quality | code-quality |
| bug predict | bug-predict |
| test gen | test-generation |
| release | release-prep |
| refactor | refactor-plan |
| doc gen | doc-gen |
If the user says "tell me more" or "go deeper"
without a new topic, call help_lookup with the
same topic again — it auto-advances to the next
level.
If the user says "start from the beginning" or "reset", call:
help_lookup(topic="<topic>", mode="progressive", reset=true)
If the user just finished a workflow, use
last_workflow to skip the concept and start at
procedural:
help_lookup(
topic="<topic>",
mode="progressive",
last_workflow="<workflow-name>"
)
For file-based warnings:
help_lookup(
topic="warnings",
mode="precursor",
file_path="<path to file>"
)
Init (/coach init)
Bootstrap a project-local help system. Two-step
Socratic flow using the help_init MCP tool.
Step 1 — Scan and propose:
help_init(action="scan")
This returns a list of proposed features with name, description, files, tags, confidence, and reason.
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.
- 8d ago First seen · 225 lines · 46 tokens per session scan A 26b25b81fa89
coach is a skill published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed today), licensed Apache-2.0. It adds 46 tokens to every session and 1,223 once invoked, about $0.0002 per session on Opus 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.
Other skills, from other repositories
aiwg-guide
Contextual AIWG help — explains current version features, answers how-to questions, routes live queries to the steward.
aiwg-help
Display all available AIWG CLI commands, their arguments, and usage examples.
eco-max
Maximum-savings variant of /eco - the same frugality rules PLUS a low reasoning-effort override for the invoked task. Use for routine chores (rename, small fix, quick question, boilerplate) when the user wants absolute minimum token spend; prefer plain /eco for hard or high-stakes work. Works in any language.
axiom-apple-docs-research
Use when researching Apple frameworks, APIs, or WWDC sessions - provides techniques for retrieving full transcripts, code samples, and documentation using Chrome browser and sosumi.ai.
learn
Learn a tech topic to a correct 101 level in minimal time. Researches open sources (official docs/releases, engineering blogs, YouTube talks, HN/Reddit, news, papers) restricted to recent material, then produces a brief with a 101 mental model, what changed, tradeoffs, an adopt/trial/hold/avoid verdict, a…
wiki-ingest
Ingest a source into the project wiki as OKF v0.2 markdown. Point at a file, PR, or doc and the wiki-curator extracts knowledge, writes YAML frontmatter, and updates relevant concept pages.