language-trap-detector
Detect ambiguous, misleading, or false-clarity language that distorts reasoning.
Skill by Alubiama
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/alubiama-language-trap-detector
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
Reviews
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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/language-trap-detector
What's inside
- Skill name
language-trap-detector- Description
- Detect ambiguous, misleading, or false-clarity language that distorts reasoning. Use when a discussion feels persuasive but slippery, or when key terms may be hiding disagreement, category errors, or vague thinking.
- License
- MIT
- Instructions
- 52 lines in SKILL.md · view on GitHub
Files (2)
- SKILL.md
- openai.yaml · agents/
SKILL.md (first lines)
# Language Trap Detector ## Goal Expose where language is creating false clarity or hidden confusion. This skill does not police wording for style. It finds where terms, categories, or phrasing are distorting the actual reasoning. ## When To Use - a claim sounds clear but unpacks poorly - debate is stuck on words rather than substance - category confusion or vague language may be hiding the real issue ## Scope Boundaries In scope: - identify ambiguous or overloaded terms - detect false precision or false clarity - restate the issue in cleaner language Out of scope by default: - copyediting for tone - full philosophical analysis ## Workflow 1. State the key sentence or claim. 2. Identify the terms carrying the reasoning. 3. Check for ambiguity, category errors, or vague success words. 4. Restate the claim more cleanly. 5. Name what question becomes clearer after the rewrite. ## Output Contract 1. `target_language` 2. `trap_terms` 3. `trap_type` 4. `clean_restatement` 5. `what_is_clearer_now` 6. `recommended_followup` 7. `next_step` ## Guardrails - Do not nitpick harmless wording. - Focus on language that changes the reasoning or decision. - Prefer cleaner framing over jargon policing.
From Alubiama/awesome-cognitive-skills, MIT.
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Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Mar 15, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
language-trap-detector skill. Agent Mart. https://agentmart.dev/skills/alubiama-language-trap-detector (last updated 2026-10-24)