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Confidence Calibration Check Agent Skill

Capture confidence ratings before and after a learning attempt to identify overconfidence and underconfidence patterns.

Install this skill Read the source first Free Written by GarethManning
Context cost
3.9k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 15.5 kBtext throughout, nothing executable
Licence
not declarednone named by its author
Last change
—v1.0
Servers it uses
Noneruns standalone

What it does

Capture confidence ratings before and after a learning attempt to identify overconfidence and underconfidence patterns. Use when a student wants to understand how well they actually know something versus how well they think they know it.

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

calibrationconfidencedocumentationmetacognitionoverconfidenceself-monitoring
Filed under

Learning & Documentation

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md15.5 kB · preview
--- # AGENT SKILLS STANDARD FIELDS (v2) name: confidence-calibration-check disable-model-invocation: false user-invocable: true effort: light # DOMAIN 20 FIELDS skill_id: "student-learning/confidence-calibration-check" skill_name: "Confidence Calibration Check" domain: "student-learning" domain_number: 20 version: "1.0" audience: "student" evidence_strength: "moderate" evidence_sources: - "Bjork & Bjork (2011) — Making things hard on yourself: the illusion of competence via re-reading" - "Koriat & Bjork (2005) — Illusions of competence in monitoring one's knowledge during study" - "Thiede et al. (2003) — Accuracy of metacognitive monitoring affects learning of texts" - "Dunning & Kruger (1999) — Unskilled and unaware of it: how difficulties in recognising one's own incompetence lead to inflated self-assessments" - "Hacker et al. (2008) — Test prediction and performance in a classroom context" input_schema: required: - field: "topic_or_question" type: "string" - field: "context" type: "string" optional: - field: "prior_calibration_data" type: "array" - field: "developmental_band" type: "string" evidence_captured: cognitive_gate: "calibration" student_attempt_required: true confidence_before: true confidence_after: true hint_level_reached: "not_applicable" error_type: "not_applicable" ai_support_type: "question | warm_start" reflection_captured: true transfer_check: "not_applicable" unassisted_followup: "not_scheduled" assistance_tag: "scaffolded" chains_well_with: - "student-learning/retrieve-first-gate" - "student-learning/explain-first-interrogator" - "student-learning/ai-claim-checker" - "student-learning/srl-session-wrapper" - "student-learning/unassisted-evidence-checkpoint" tags: ["metacognition", "calibration", "confidence", "self-monitoring", "overconfidence"] ---
60# Confidence Calibration Check
61
62## What This Skill Does
63
64Captures a confidence rating (0–100) before a knowledge attempt and again after receiving feedback, then compares the two. The AI identifies and names the pattern: overconfidence (high confidence + poor performance) and underconfidence (low confidence + good performance) are both worth surfacing. Over time, tracking calibration accuracy becomes itself a metacognitive skill — learners who can accurately predict their own knowledge gaps are significantly better at allocating study time. This skill makes the "illusion of competence" visible and actionable.
65
66## Evidence Foundation
67
68Bjork & Bjork (2011) identified the illusion of competence as one of the primary obstacles to effective self-study: re-reading material produces a feeling of familiarity that learners mistake for genuine understanding. Students leave a study session feeling more confident than their actual knowledge warrants — and they study less as a result. Koriat & Bjork (2005) demonstrated that studying with self-referential judgements (asking "do I know this?") produces systematically biased predictions in which learners overestimate their own performance, particularly when material was recently studied. Thiede et al. (2003) showed that accuracy of metacognitive monitoring directly affects learning outcomes: students who are better calibrated allocate their study time more effectively, spending more time on material they actually don't know. Dunning & Kruger (1999) documented the broader pattern: novices in a domain not only perform poorly but lack the knowledge to recognise their own performance gaps, producing inflated self-assessment. Hacker et al. (2008) found in a classroom study that students who made test predictions before sitting exams, then compared predictions to results, showed improved performance on subsequent assessments — suggesting that the comparison act itself has metacognitive training value.
69
70## System Prompt
71
72```
73You are a metacognitive coach. Your role is to help {{name_or_"the learner"}} understand the relationship between how confident they feel about their knowledge and how much they actually know — and to develop the habit of accurate self-monitoring. This is the confidence calibration check.
74
75CONTEXT: {{context}}
76TOPIC OR QUESTION: {{topic_or_question}}
77PRIOR CALIBRATION DATA: {{prior_calibration_data — if not provided, treat this as a first calibration check}}
78DEVELOPMENTAL BAND: {{developmental_band — if not provided, assume secondary school / undergraduate}}
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md2,261 words
Files1
Licencenot declared
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈610
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
3,265
on trigger
The instruction body, read only when the skill fires.
1.9%
of a 200k window
Ten skills this size would take about 19% of the window before you open a file.
050k100k150k200k context window

3.9k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Middling. Fine to keep on in a project where you use it weekly, worth unloading in one where you never do.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

1 file, 15.5 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md15.5 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 1 file you can review in full before installing.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# Confidence Calibration Check · 3.9k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/confidence-calibration-check/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/confidence-calibration-check" ] && { [ ! -e .claude/skills/confidence-calibration-check ] || { mv .claude/skills/confidence-calibration-check "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/confidence-calibration-check" .claude/skills/ && echo "Installed .claude/skills/confidence-calibration-check"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add garethmanning/confidence-calibration-check

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/confidence-calibration-check/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/confidence-calibration-check/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/confidence-calibration-check" ] && { [ ! -e ~/.claude/skills/confidence-calibration-check ] || { mv ~/.claude/skills/confidence-calibration-check "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/confidence-calibration-check" ~/.claude/skills/ && echo "Installed ~/.claude/skills/confidence-calibration-check" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/confidence-calibration-check/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Version1.0
Publishedno release date on file
PriceFree
Referencegarethmanning/confidence-calibration-check

Versions

v1.0 is what is on the shelf; no release here carries a date. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

v1.0
  • No earlier releases have been published to the marketplace.
Pinning

The install command always fetches the release that is current the day you run it — v1.0 today — and cannot ask for an earlier one. The copy on your disk does not change until you run it again.

Reviews

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Who wrote it

GA
GarethManning

Publishes on mcprush.

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