calibrated-inference
When asked to estimate something unstated, produce a legible correctable evidence chain rather than refusing or fabricating a number.
Skill by Kalabint
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/kalabint-calibrated-inference
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: ml
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/calibrated-inference
What's inside
- Skill name
calibrated-inference- Description
- When asked to estimate something unstated, produce a legible correctable evidence chain rather than refusing or fabricating a number.
- License
- AGPL-3.0
- Instructions
- 9 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Calibrated inference "Refuse because it is not certain" and "state a confident number from nowhere" are both failures. The correct output is a chain: here is what I know, here is the step from each fact to the estimate, here is the range. **Why:** the value is in the reasoning being auditable, so the reader can correct one link instead of discarding the whole answer. **How to apply:** show the inputs, the transform, and the uncertainty. Make each step something the reader could point at and call wrong. Prefer a wide honest range to a narrow invented one.
From Kalabint/llm-tooling, AGPL-3.0.
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Signals
- Stars
- 6
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 7, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- AGPL-3.0
- Repository
- github.com/Kalabint/llm-tooling
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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handoff
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Read OR write the project's session-handoff doc.
SkillBFreshness: B★ 6Claude Code +9 - 0.582score
memory-audit
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Audit the project's persistent agent memories for backfire-risk, stale/superseded state, contradictions, redundancy, and bloat.
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prepare-next-steps
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Trigger when user asks to "prepare next steps", "prep next steps", or signals readiness for autonomous build ("before we build", "pre-flight").
SkillBFreshness: B★ 6Claude Code +9 - 0.574score
no-sycophancy
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Strip praise, flattery, and manufactured agreement from output so the signal is the fact, not the framing.
SkillBFreshness: B★ 6Claude Code +9 - 0.574score
no-unmeasured-numbers
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State no number without an instrument behind it - no duration or effort estimates, no usage forecasts, no unbaselined comparatives.
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Cite this page
calibrated-inference skill. Agent Mart. https://agentmart.dev/skills/kalabint-calibrated-inference (last updated 2026-10-24)