macrothink — Claude Code skill: fresh reads on your current path
The skill fans out 2 to 5 fresh reads of the stripped-down problem and reports where they diverge from the session's direction, divergence first.
npx skills add LilMGenius/paperthin --skill macrothink -a claude-codeWhat macrothink does
macrothink is user-invoked and read-only. It looks at the decision the session is about to keep building on, not at the artifact that describes it, and checks whether that direction inherited a framing from examples, wording or earlier turns.
The workflow names the current direction, then strips the prompt down to the underlying problem: goal, constraints, known facts. Examples, the suggested answer, preferred naming and framing-specific wording come out. From there it fans out 2 to 5 independent fresh reads, 3 by default. Same model is allowed, because the pass hunts for session-framing blind spots rather than model-independent truth. Every read gets classified as divergent-incompatible, divergent-compatible or convergent, and the report leads with the incompatible ones.
When several divergences point the same way, the skill names the shared root and files the individual reads under it as evidence. Convergence is labelled reassurance, never proof, since agreement between reads of one model certifies nothing. Nothing fires automatically here; the skill only runs on an explicit call. What comes back is candidates and risks. It does not rewrite the plan or pick the final answer.
What it helps with
- catch a blind spot in a framing the session inherited from earlier turns
- check a decision that fresh reads agree on a little too easily
- see which premises of the direction break under an independent read
- collapse several similar divergences into the one root behind them
- separate reassurance from proof before building further
Example prompts for the agent
- run macrothink and check whether the current direction is tunnel-visioned
- macrothink on the decision we're about to keep building on
- macrothink: fan out 3 fresh reads of the problem and report divergences first
How to install macrothink
1Skills CLI (Vercel)
npx skills add LilMGenius/paperthin --skill macrothink -a claude-code2Manually: put the files in place
~/.claude/skills/macrothink/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/macrothink/
1Skills CLI (Vercel)
npx skills add LilMGenius/paperthin --skill macrothink -a codex2Manually: put the files in place
.agents/skills/macrothink/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add LilMGenius/paperthin --skill macrothink -a cursor2Manually: put the files in place
.cursor/skills/macrothink/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install LilMGenius/paperthin macrothink2Manually: put the files in place
.github/skills/macrothink/SKILL.md1Skills CLI (Vercel)
npx skills add LilMGenius/paperthin --skill macrothink -a gemini-cli2Platform CLI
gemini skills install https://github.com/LilMGenius/paperthin --path skills/depth/macrothinkManually: put the files in place
.devin/skills/macrothink/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add LilMGenius/paperthin --skill macrothink -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about macrothink
How do I install macrothink in Claude?
Run npx skills add LilMGenius/paperthin --skill macrothink -a claude-code. The skill file lands at ~/.claude/skills/macrothink/SKILL.md.
What does macrothink do?
It strips the session's framing, fans out 2 to 5 fresh reads of the restated problem and classifies each one against the current direction. Divergent-incompatible findings come first in the report.
Does convergence prove the direction is right?
No. The skill allows the same model for every read, so it treats agreement as reassurance rather than proof. It also refuses to pick a winner by majority or averaging.
Source text
SKILL.md · MIT
--- name: macrothink disable-model-invocation: true description: "User-invoked read-only pass for checking whether the current direction is tunnel-visioned: strip the session's bait, fan out 2 to 5 same-model fresh reads, and report divergence first without treating convergence as proof." --- Step back from the session's chosen path and ask several fresh reads what the current direction might be missing. ## Goal `macrothink` checks the live decision or direction in hand, not the artifact that describes it. It is for moments when the session may have inherited a framing from examples, wording, prior turns, or a first plausible answer. The product is a spread of independent reads. Divergence is the signal. Convergence is reassurance, never proof. ## Workflow This skill is not model-invoked automatically. When a user explicitly invokes it, the invoked run may create the bounded fresh sub-sessions below; they are read-only inputs to this pass, not separate authority to change the plan. 1. Name the current direction: the decision the session is about to keep building on. 2. Strip the prompt to the underlying problem: goal, constraints, and known facts. Remove the session's own examples, suggested answer, preferred naming, and framing-specific wording. 3. Fan out independent fresh reads of that stripped restatement: **2 to 5, default 3**. Same model is allowed because this pass does not claim cross-model verification. 4. Collect each read without correcting it toward the session's current direction. 5. Classify each read against the current direction: - `divergent-incompatible`: challenges a premise the direction depends on. - `divergent-compatible`: adds or reframes something useful without discarding the direction. - `convergent`: independently lands near the current direction. 6. Cluster before reporting: when several reads diverge in the same direction, name the shared root they point at — the pattern behind the divergences is the finding, and the individual reads sit under it as evidence. Do not report five specifics that are one gap seen five times. 7. Report `divergent-incompatible` first, then `divergent-compatible`, then `convergent`. Label convergence as reassurance only. 8. Return control to the main session. This skill is read-only and advisory; it does not rewrite the plan or pick the final answer. ## Rules - **Divergence first.** The most important output is the strongest `divergent-incompatible` finding, if any. - **Roots over instances.** A spread of specific divergences that share one underlying gap is one finding, not many; naming the root is what makes the pass actionable beyond the cases the reads happened to hit. - **No majority vote or averaging.** Do not pick a winner by count, smooth away disagreement, or present agreement as consensus. - **Same model is allowed.** The pass looks for session-framing blind spots, not model-independent truth. - **User-invoked fan-out only.** Do not trigger this skill automatically. If the user invokes it, bounded read-only fresh sub-sessions are allowed to produce the required reads. - **Not consensus verification.** Do not say the direction is verified, proved, validated, or settled by same-model convergence. - **Convergence is reassurance, not proof.** It means this pass did not surface a better angle; it does not certify correctness. - **Read-only / advisory.** Surface candidates and risks; leave decisions and edits to the main workflow. ## Verification Before finishing, confirm: 1. The restatement removed the session's bait while preserving real constraints. 2. Every read was classified as `divergent-incompatible`, `divergent-compatible`, or `convergent`. 3. Divergences sharing one root were reported as that root, with the individual reads as evidence under it. 4. The report put divergent-incompatible findings first. 5. Any convergence was described as reassurance, not proof. 6. The report did not use consensus, majority, averaging, verified, or proved wording.
© LilMGenius · MIT · LilMGenius/paperthin