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From skills-for-humanity
Audits claims in a domain by assigning explicit epistemic statuses (known, believed, assumed, hoped) to separate confidence from correctness.
npx claudepluginhub human-avatar/skills-for-humanityHow this skill is triggered — by the user, by Claude, or both
Slash command
/skills-for-humanity:s4h-epistemology-epistemic-statusThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Most thinking conflates knowing with believing, believing with assuming, and assuming with hoping. These are not the same thing. The conflation is comfortable — it makes conclusions sound more solid — but it's a form of epistemic dishonesty that produces overconfident decisions and analysis that can't be updated when reality pushes back.
Analyzes the nature, structure, and limits of knowledge. Routes to the appropriate sub-skill for clarifying what kind of claim is being made, what would justify belief, or how certain one can be. Use when investigating epistemic questions.
Calibrates AI confidence to evidence, flagging uncertainty and limitations before presenting conclusions. Useful when accuracy matters or knowledge is partial.
Decomposes critical decisions into falsifiable claims, verifies load-bearing ones with fresh subagents and external evidence, argues the opposition, and records a verdict.
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Most thinking conflates knowing with believing, believing with assuming, and assuming with hoping. These are not the same thing. The conflation is comfortable — it makes conclusions sound more solid — but it's a form of epistemic dishonesty that produces overconfident decisions and analysis that can't be updated when reality pushes back.
Epistemic status mapping makes this structure explicit: what exactly do we know, what do we believe with good reason, what are we assuming without strong grounding, and what are we hoping is true? The goal is not skepticism — it's honesty that produces better decisions.
Step 1: Inventory All Claims in Play List every claim that the argument, plan, analysis, or domain rests on. Be exhaustive. Include:
Resist the urge to prune. The point is to surface everything before classifying anything.
Framing check: Confirm the specific domain being audited before continuing. State what you've identified — the actual argument, plan, or body of claims under examination and its central purpose — in one sentence, then use AskUserQuestion:
Step 2: Assign Epistemic Status
Use this taxonomy:
| Status | Meaning | Test |
|---|---|---|
| Known | Established by strong evidence, replication, or logical necessity | Would hold up under adversarial scrutiny from a well-informed skeptic |
| Reasonably believed | Well-supported but not certain; evidence is good but not definitive | Rational to act on; would update if strong contrary evidence appeared |
| Assumed | Taken for granted without explicit verification; may or may not be true | Could be wrong; hasn't been checked; often invisible because it seems obvious |
| Hoped | Believed partly because we want it to be true | Motivated reasoning may be distorting confidence; should be treated with extra skepticism |
| Unknown | Genuinely unclear; no basis for confident assignment | The honest answer is "we don't know" |
Assign one status per claim. If you're unsure which status applies, that uncertainty is itself epistemic information — note it.
Step 3: Identify Dependency Chains Map which claims depend on which others. Then flag: where do high-confidence claims rest on lower-confidence foundations?
This is the critical finding. It's common for a conclusion labeled "known" to rest on a chain where one link is "assumed" or "hoped." The conclusion inherits the weakest status in its dependency chain.
Step 4: Audit for Status Inflation Review the inventory for common patterns of epistemic overconfidence:
Step 5: Flag High-Stakes Unknowns Which unknown or hoped claims are most load-bearing? If the thing you most need to be true turns out to be false, what breaks?
Before narrowing: Show the complete set of unknown and hoped claims to the user first. Use AskUserQuestion:
These are the priority items for investigation, verification, or contingency planning.
Step 6: Produce the Map Synthesize into a structured output: the full inventory with statuses, the dependency structure, and the highest-priority epistemic gaps.
Before proceeding, use the AskUserQuestion tool. State your interpretation of the situation in 1–2 sentences — what is being analyzed and what the core question is — then ask:
Proceed based on their selection. If the user reframes, incorporate the correction before running any analysis.
[What is being audited]
| Claim | Status | Notes |
|---|---|---|
| [Claim 1] | Known / Reasonably Believed / Assumed / Hoped / Unknown | [Why this status; what would change it] |
| [Claim 2] | ... | ... |
| ... |
High-confidence claims resting on lower-confidence foundations:
| Unknown / Hoped Claim | Why It's Load-Bearing | Priority |
|---|---|---|
| [Claim] | [What depends on it] | High / Medium / Low |
[One paragraph: what is the honest picture of what's known vs. assumed in this domain, and what are the 1-2 highest priority epistemic gaps to address?]
This skill maps confidence across a domain — use epistemology-justification to go deep on the structure of a single belief's support chain. Use epistemology-limits when a claim is unknown not due to lack of investigation but due to a fundamental or structural limit on what can be established. Use probability when the goal is to quantify uncertainty numerically rather than categorize it epistemically.
After delivering this output, use AskUserQuestion to offer the next move:
/s4h-epistemology-limits — Map where the knowledge runs out beyond the current status/s4h-probability-confidence-calibration — Calibrate expressed confidence to match epistemic status/s4h-investigation-evidence-audit — Audit the evidence underpinning the lowest-status claims