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 deciqAI/knowledge-skills --skill checklistgit clone --depth 1 https://github.com/deciqAI/knowledge-skillsWrote 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/deciqai/knowledge-skills/checklist)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/checklist"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/checklist/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/deciqai/knowledge-skills/checklist"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/checklist.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 | $0.00105 | $0.01803 |
| Opus 5.5 | $0.00042 | $0.00721 |
| Sonnet 5.5 | $0.00021 | $0.00361 |
| Haiku 4.5 | $0.00011 | $0.00180 |
Grade A, and why
checklist 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Checklist
Overview
A checklist is a short written list of must-not-skip steps for a complex repeated operation. It externalizes working memory — which fails under load, ego, time pressure, and fatigue — so attention stays on the situation rather than step recall. Boeing 1935 → Pronovost ICU 2001 → WHO Surgical 2008: each produced 36-47% reductions in major adverse events at near-zero cost.
Composes with metacognition, confirmation-bias, cognitive-load-theory, premortem, inversion.
When to Use
- High-stakes repeated operations (deployments, launches, M&A close, hiring decisions, financial close)
- Multiple steps where skipping one costs far more than running the checklist
- Multi-person operations where coordination must be consistent
- New team members joining a critical workflow
- Shipping or updating an AI agent / model version in production — evals, guardrails, spend caps, rollback: known steps that skilled teams skip under deadline
Not when: operation is simple/one-off; no recurring pattern exists; checklist culture creates false confidence (mechanical checking without thought).
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a specific operation → run The Process directly.
- Coach mode: user is new to the framework → guide step by step.
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
- One-line: for any complex repeated operation, a 6-10 item checklist outperforms expert memory under load — it externalizes the steps that fail systematically.
- Check fit: repeated + high-stakes + consequential errors = checklist candidate. Simple or one-off = skip.
- Elicit their real case: what operation, where does it fail, what near-misses have occurred?
[WAIT — do not advance until user responds]
What ships with it
4 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.
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 · 125 lines · 105 tokens per session scan A 2ef8ac8d860f
checklist is a skill published in the GitHub repository deciqAI/knowledge-skills (13 stars, last pushed 1mo ago), licensed MIT. It adds 105 tokens to every session and 1,803 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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