metacognition

A reasoning checkpoint system that makes the agent review its understanding, evidence, scope, approach, and stopping conditions at important moments.

In plain words
What is it for?
Use it when starting repository work, changing direction, encountering unexpected evidence, finishing a major phase, or considering an irreversible action.
Why use it?
It helps prevent unsupported assumptions, unnecessary work, scope growth, and claims of completion without observable proof.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/shinpr/agentic-code/metacognition
Any agent
npx skills add shinpr/agentic-code --skill metacognition
Clone the repo
git clone --depth 1 https://github.com/shinpr/agentic-code

Made for: Claude Code, Codex.

Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 543 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00040 $0.00543
Opus 5 $0.00020 $0.00271
Sonnet 5 $0.00008 $0.00109
Haiku 4.5 $0.00004 $0.00054

Measured 2d ago against content hash d4745f5b337d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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.

.agents/skills/metacognition/SKILL.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Metacognition Protocol

Purpose

Prevent the agent from following an invalid route, expanding work without evidence, or declaring completion without observable proof.

Checkpoints

Run a checkpoint when:

  • repository work begins;
  • the task type or approved outcome changes;
  • unexpected evidence invalidates the current approach;
  • a major phase or coherent implementation task completes;
  • the next action requires user authority or an irreversible operation.

Routine reversible actions inside an already validated approach do not require a separate checkpoint.

Assessment

Outcome and Scope

  • What observable outcome owns this work?
  • Which requirements are current, and which items are current-state evidence or speculation?
  • What non-goals and contracts must remain unchanged?
  • Could reuse or no-change already satisfy the outcome?

Evidence

  • Which claims are observed, inferred, or unknown?
  • What repository rule or pattern governs the next decision?
  • Does an unknown change the outcome, scale, major design, authority, or verification?

Approach

  • Is the current route the smallest sufficient one?
  • Does every added artifact, mechanism, test, gate, or task change the outcome, protect a boundary, serve a consumer, or supply necessary proof?
  • What current evidence would make the approach invalid?

Completion

  • Is the requested result observable?
  • Did the applicable established checks pass?
  • Are verification gaps and residual limitations reported?
  • Did review findings remain within approved scope?

Decision

After assessment, choose one:

  • continue: Current evidence supports the route.
  • adjust: A reversible local change keeps the approved outcome intact.
  • return to owning phase: Evidence invalidates a requirement, major design decision, task boundary, or verification strategy.
  • ask the user: Progress requires a new requirement, scope change, unavailable authority, or unauthorized irreversible action.
  • complete: The outcome and required proof are observable.

Read the full file on GitHub · 77 lines

Changes

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.

  1. 2d ago First seen · 77 lines · 40 tokens per session scan A d4745f5b337d

Subscribe to this mod's changes

metacognition is a skill published in the GitHub repository shinpr/agentic-code (49 stars, last pushed 4d ago), licensed MIT. It adds 40 tokens to every session and 543 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 2026-08-30.