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SKILL verified MIT Self-run

Consensus Mapping

skill-skyf0xx-better-thinking-consensus-mapping · by skyf0xx

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Install

$ agentstack add skill-skyf0xx-better-thinking-consensus-mapping

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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Reliability & compatibility

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Declared compatibility

Claude CodeClaude Desktop

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About

Consensus Mapping

Measure the actual gradient of agreement across a group instead of forcing a binary vote that hides where the real disagreement lives.

Why

A binary vote collapses a spectrum of "strongly for" to "strongly against, will actively block" into a single number, hiding both near-unanimous soft support and a small but intense veto-level objection. Mapping the gradient makes the group's real state visible before it's acted on.

Use when / Don't use when

  • Use when: a group decision needs real buy-in, not just a nominal majority; a quick vote feels like it's hiding real dissent.
  • Don't use when: a simple majority vote is genuinely sufficient and buy-in from the minority isn't required for implementation to succeed.

Inputs → Outputs

  • Inputs: a group facing a decision with varying levels of agreement.
  • Outputs: a gradient map of the group's position, with any veto-level objections surfaced explicitly rather than averaged away.

Principles

  • Use a gradient scale — enthusiastic support, support with reservations, neutral, disagree but will go along, block — rather than binary yes/no.
  • A single strong "block" carries different weight than several "reservations" and should be surfaced, not averaged into the mean.
  • The goal is often not unanimous enthusiasm but the absence of unaddressed blocking objections.

Procedure

  1. State the proposal precisely enough to be rated.
  2. Have each participant rate their position on a gradient scale, ideally simultaneously, to avoid anchoring on the first vocal response.
  3. Map the distribution: where does the group cluster, and where's the spread?
  4. Surface any block-level objections explicitly — don't let them wash out in an averaged score.
  5. For blocks or strong reservations, understand the underlying concern before proceeding.
  6. Decide: proceed with addressed concerns noted, revise the proposal, or escalate if a genuine block remains.

Common mistakes

  • Converting the gradient back into a binary average, hiding exactly what the technique was meant to surface.
  • Letting the loudest objector's position stand in for the whole group's gradient.
  • Using this technique for decisions where genuine buy-in isn't actually necessary.

Examples

  • A team deciding on a technical direction.
  • A co-op's governance vote.
  • A jury's deliberation check-in before a final verdict push.

Related

  • [[interest-based-bargaining]] — the technique for resolving a surfaced block-level objection.
  • [[retrospective-facilitation]] — uses this mapping when a retro's interpretation is contested.
  • [[session-design]] — determines when this technique belongs in a session's agenda.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.