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 metacognitiongit 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/metacognition)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/metacognition"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/metacognition/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/metacognition"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/metacognition.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 | $0.00108 | $0.02333 |
| Opus 5 | $0.00054 | $0.01167 |
| Sonnet 5 | $0.00022 | $0.00467 |
| Haiku 4.5 | $0.00011 | $0.00233 |
Grade A, and why
metacognition 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 9d 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Metacognition
Overview
Metacognition is the live monitoring loop during reasoning — "am I doing this right now; what strategy am I using; should I switch?" — not after-the-fact reflection. Coined by Flavell (1979); operationalized by Pólya's 1945 four-stage protocol; empirically validated by Schoenfeld (1985): experts spend 30–40% of problem-solving time monitoring; novices spend 5%. The expert-novice gap is less raw knowledge than this loop.
Compose: first-principles to interrogate assumptions · probabilistic-thinking to calibrate confidence · inversion to ask "how could my reasoning be wrong?" Metacognition is the background process that decides which other skills to deploy.
When to Use
Apply when:
- Stuck > 15 minutes with no progress — the most reliable trigger
- Analysis feels confident but suspiciously fast (speed without monitoring = invisible errors)
- Same kind of mistake keeps recurring across problems
- Cannot tell whether you understand a topic or just recognize it (illusion of fluency)
- Deciding whether to trust an AI copilot's fluent answer or slow down and verify it (AI adoption, automation complacency, "should I trust the AI here")
- Someone says: "metacognition," "calibration," "am I stuck on the right problem," "I should know this but I don't"
When NOT to use: routine fluent tasks; real-time emergencies; creative flow states; already-overactive worriers who would spiral.
Coaching Novices (Adaptive Front Door)
- Engine mode: concrete reasoning task → run The Process directly.
- Coach mode: user unfamiliar or no concrete case → 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 what-it-is: metacognition is paying attention to how you are thinking while you think — catching when you're stuck, when confidence outruns understanding, when you should switch tactic. Experts spend 30–40% of problem-solving time on this loop; novices 5%.
- Check fit against When to Use / When NOT to use. Routine task / flow / over-worrier → redirect.
- Elicit their real case — a specific problem they're stuck on, an analysis they're running, or a decision they're making. "I'm thinking about my career" is too vague; need something concrete.
[WAIT — do not advance until user responds]
- Run The Process one stage at a time with their input. Pause at each stage for their answer.
[WAIT — do not advance until user responds]
- Close by naming the specific monitoring move they used (or skipped). They leave knowing the exact question to ask themselves next time.
[WAIT — do not advance until user responds]
What ships with it
3 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.
- 9d ago First seen · 124 lines · 108 tokens per session scan A 6d2dd3c5c26c
metacognition is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 108 tokens to every session and 2,333 once invoked, about $0.0005 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 2026-09-03.
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