Chalk Labs
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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/human-avatar-s4h-analogy
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
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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/s4h-analogy
What's inside
- Skill name
s4h-analogy- Description
- Entry point for the analogy toolkit. Routes to the right analogy skill based on your situation. Use when you say 'analogy', 'is this like that', 'find a comparison', 'import a solution from elsewhere', 'fresh eyes on this', 'where does this metaphor break', or want analogical reasoning applied without knowing which specific tool fits.
- License
- MIT
- Instructions
- 86 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Analogy Applies analogical reasoning to any problem. Diagnoses what kind of analogy work is needed and applies the right tool. ## Which tool fits | You need to... | Tool | |---|---| | Find where an existing analogy or metaphor breaks down | boundary-testing | | Import solutions from a completely different domain | domain-transfer | | Approach a problem through a different field's lens | perspective-shifting | | Test the structural correspondence between two situations | structure-mapping | ## Routing Decision - **Already using an analogy and want to stress-test it** → boundary-testing - **Stuck on a problem, want to find who's solved something like it elsewhere** → domain-transfer - **Need fresh eyes from an expert in a different field** → perspective-shifting - **Want to know if two situations are genuinely structurally similar** → structure-mapping - **Unclear** → structure-mapping first (establishing the analogy rigorously), then boundary-testing (finding where it fails) **Framing check:** Confirm the specific analogy situation before routing. State what you've identified — the analogy or problem being examined and the goal (stress-test, import solutions, shift perspective, or validate structure) — in one sentence, then use `AskUserQuestion`: - **Question:** "I'm reading this as: [your one-sentence framing of the analogy situation and goal]. Is that right?" - **Header:** "Framing" - **Options:** - **Yes — proceed** — framing is correct - **Adjust** — one element is off; user will correct it before you continue - **Reframe** — different situation than read; incorporate the correction before proceeding --- ## Confirm Direction After diagnosing which tool fits, use the `AskUserQuestion` tool to confirm direction. Construct the question dynamically to include your diagnosis: - **Question:** "My read: **[diagnosed tool]** — [one sentence on why it fits]. How would you like to proceed?" - **Header:** "Direction" - **Options:** - **Yes, run that tool** — Execute the diagnosed skill immediately using the context already provided - **Show all options** — List every skill in this category with one-line descriptions - **Quick version** — Run a lighter-weight alternative if one exists for this situation - **Re-diagnose** — Revisit the situation description for a different read Proceed based on their selection. --- ## Boundary Testing *Finds where an analogy breaks down before it's relied upon.* Name the analogy explicitly: A is like B because [shared properties]. Now systematically test each dimension of the comparison. For each shared property: does it actually hold? What differences exist? Find the dimension where the analogy fails in a way that matters for the decision at hand. Analogies fail silently — the damage happens when decisions are made on a mapping that doesn't hold in the relevant dimension. **Output:** Analogy map (what holds, what doesn't), the specific dimension of failure, and what decisions should not rely on this analogy. --- ## Domain Transfer *Imports solutions from unrelated domains by finding structural similarities.* Name the core structure of the problem: what kind of challenge is this underneath the surface details? Search for domains that have solved structurally similar problems — often in completely unrelated fields (biology for network design, military strategy for resource constraints, jazz for improvisational systems). For each candidate domain: what was the solution? How does it map back? **Output:** Core problem structure, candidate domains with solved analogues, and specific solutions mapped back to the original problem. --- ## Perspective Shifting *Approaches a problem through a completely different field's lens.* Name the home domain — the expertise lens being applied by default. Now select 2-3 radically different fields: what would a [biologist / game designer / urban planner / etc.] see when looking at this? Apply each lens genuinely, not superficially. The goal is to surface assumptions invisible from inside the home domain. **Output:** Per-lens analysis — what each field notices, what assumptions it challenges, what solutions it suggests that the home domain wouldn't. --- ## Structure Mapping *Identifies the deep structural correspondence between two situations.* List the elements of situation A. List the elements of situation B. For each element in A: does a corresponding element exist in B? Are the relationships between elements preserved? Test whether the mapping is genuine isomorphism or just surface similarity. Surface similarity fails on deeper structure; genuine isomorphism predicts behavior accurately. **Output:** Element-by-element correspondence table, relationship preservation check, verdict on whether the analogy is structurally valid, and what the mapping predicts.
From human-avatar/skills-for-humanity, MIT.
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Signals
- Stars
- 235
- Forks
- 24
- Open issues
- 0
- Last commit (this folder)
- May 31, 2026 (5 months ago)
- Last release
- May 31, 2026 (5 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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Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
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Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
s4h-analogy skill. Agent Mart. https://agentmart.dev/skills/human-avatar-s4h-analogy (last updated 2026-10-24)