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 pjt222/agent-almanac --skill attunegit clone --depth 1 https://github.com/pjt222/agent-almanacWrote 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/pjt222/agent-almanac/attune)<a href="https://agentmods.dev/skills/pjt222/agent-almanac/attune"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/attune/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/pjt222/agent-almanac/attune"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/attune.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00092 | $0.02218 |
| Opus 5.5 | $0.00037 | $0.00887 |
| Sonnet 5.5 | $0.00018 | $0.00444 |
| Haiku 4.5 | $0.00009 | $0.00222 |
Grade A, and why
attune 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attune
Calibrate to the person — read communication style, expertise depth, emotional register, and implicit preferences from conversational evidence. Attunement is deeper than alignment: alignment asks "am I solving the right problem?" Attunement asks "am I meeting this person where they are?"
When to Use
- At the start of a new session — calibrate before the first substantive response
- When communication feels mismatched — too formal, too casual, too detailed, too sparse
- After unexpected feedback — the mismatch reveals an attunement gap
- When transitioning between very different contexts (e.g., technical debugging to creative brainstorming)
- When MEMORY.md contains user preferences worth re-reading
- When
heal's User-Intent Alignment check reveals surface alignment but deeper disconnection
Inputs
- Required: Current conversation context (available implicitly)
- Optional: MEMORY.md and project CLAUDE.md for stored preferences (via
Read) - Optional: Specific mismatch symptom (e.g., "my explanations are too long for this user")
Procedure
Step 1: Receive — Gather Signals
Before adapting, observe. Attunement begins with reception, not analysis.
- Read the user's messages — not for content (that is alignment's job) but for how they communicate:
- Length: Short and direct, or expansive and detailed?
- Vocabulary: Technical jargon, plain language, or mixed?
- Tone: Formal, casual, warm, efficient, playful?
- Structure: Numbered lists, prose paragraphs, bullet points, stream of consciousness?
- Punctuation: Precise punctuation, emoji, ellipses, exclamation marks?
- Notice what the user does not say — what they skip, what they assume you know, what they leave implicit
- If MEMORY.md or CLAUDE.md is available, check for stored preferences — they represent patterns stable enough to record
Got: A picture of how this person communicates — not a psychological profile, but a communication fingerprint. Enough to match their register.
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 · 166 lines · 92 tokens per session scan A 72d4289179c0
attune is a skill published in the GitHub repository pjt222/agent-almanac (42 stars, last pushed 5d ago), licensed MIT. It adds 92 tokens to every session and 2,218 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 2026-09-03.
Other skills, from other repositories
audit-pr
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execute-phase
Step executor for units whose triage (unit-lane) decided which steps the unit needs. Implements one triaged step (or all remaining steps), with frozen acceptance, step-local gates, commits, red-gate repair, and diff-size guard. BREAKING: replaced PLAN.md/TASKS.md/progress.md/ACCEPTANCE.md with the unit doc's Tasks…
fold-findings
Repair persisted fix-now findings in compatible atomic batches: root-cause fixes, green gate, commit/push, and per-row folded: yes updates. Never reclassify or substitute backlog notes. Triggers: "fold-findings", "fix the review findings", "repair audit blockers".
init-workspace
Adapt the workflow scaffold to a new repository or add only missing substrate blocks to an existing install. Every install, hook, and overwrite needs explicit consent. Triggers: "init-workspace", "set up agentic workflow", "upgrade workflow scaffold".
product-audit
Audit the whole product across code, quality, process, docs, roadmap, and tooling; it owns the repo-wide bug hunt, security research, and broken-version investigation (scoped and budgeted per dimension, as distinct from review-change's change-scoped review). Persist one severity-ranked, F-numbered report with…
review-change
Review a change with only applicable internal axes, classify every finding, persist fix-now work, and return one evidence-backed decision. Findings only; --adversarial N uses isolated reviewers; --synthesize fuses supplied reviewer tables. Triggers: "review-change", "review this change", "adversarial review".