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Think Evidence Vs Inference Sort

skill-product-on-purpose-thinking-framework-skills-think-evidence-vs-inference-sort · by product-on-purpose

Produces an evidence/inference ledger by sorting the claims in a prompt, document, or proposed conclusion into evidence, inference, and assumption, attaching a confidence level to each inference and flagging anything uncited. Use when a recommendation must be trusted, or when you need to audit the reasoning behind a conclusion in a high-stakes context.

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Install

$ agentstack add skill-product-on-purpose-thinking-framework-skills-think-evidence-vs-inference-sort

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Security review

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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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About

Evidence vs Inference Sort

Reasoning degrades when evidence (what is actually observed or verifiable) is blended with inference (what is deduced) and assumption (an unstated premise). Models are especially prone to this: they present fluent inference in the same confident register as fact. This skill separates them: it labels each claim in a body of text as evidence, inference, or assumption, records the basis for each, attaches a confidence level to inferences, and flags anything uncited. The output is an evidence/inference ledger. Note the boundary: this classifies claim type; it does not verify that the evidence is true (that is a separate, fact-checking job).

When to Use

  • A recommendation, plan, or conclusion must be trusted before it is acted on.
  • High-stakes contexts: legal, medical, financial, safety, architecture and planning.
  • Auditing the reasoning behind a conclusion, including the agent's own.
  • As a step in a reasoning-audit workflow.

When NOT to Use

  • As a fact-checker. It labels what kind of claim something is, not whether it is true.
  • On creative or exploratory work where rigor is not the point.
  • On trivial claims, where sorting produces only noise.
  • When the claims are already well-sourced and the leaps are already explicit.

Instructions

When asked to sort evidence from inference, follow these steps:

  1. Collect the claims. Break the prompt, document, or proposed conclusion into discrete claims. Keep each to one assertion.
  2. Label each claim. Mark it Evidence (observed or verifiable, with a source), Inference (deduced from other claims), or Assumption (an unstated premise it depends on).
  3. Record the basis. For evidence, name the source or observation. For inference, name what it is inferred from. For assumption, state the premise plainly.
  4. Rate inference confidence. For each inference, assign high / medium / low and say why. Do not treat plausibility as verification.
  5. Flag the gaps. Mark anything presented as fact but uncited, and any load-bearing assumption that is unexamined.
  6. Surface the load-bearing unknowns. List the few unsupported claims that most need verification before the conclusion is trusted.
  7. Emit the ledger per references/TEMPLATE.md.

Output Format

Use the template in references/TEMPLATE.md. The deliverable is the ledger plus the load-bearing-unknowns list, not prose.

Quality Checklist

Before finalizing, verify:

  • [ ] Every claim is labeled evidence, inference, or assumption.
  • [ ] No confident inference is mislabeled as evidence.
  • [ ] Inferences carry a confidence level with a reason.
  • [ ] Uncited "facts" and unexamined assumptions are flagged.
  • [ ] The output does not claim to have verified truth, only sorted claim type.
  • [ ] The output is the ledger artifact, not prose.

Evidence

Tier P. The evidence/inference distinction is a foundational critical-thinking competence (Facione, Delphi Report 1990), and explicit critical-thinking instruction shows moderate gains broadly (strongest for argument mapping, an adjacent technique). This specific "sort into a ledger" method is practitioner-grade, evidence is transferred from human contexts, and the skill verifies claim type, not truth. Full grading: evidence/dossier.md.

Examples

See references/EXAMPLE.md for a completed ledger.

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.