clarify
Skill5 starsChanged 43 days agoMITView on GitHub
Decides whether to ask clarifying questions or proceed with an answer, optimizing for information value vs. delay cost. Now with mathematical depth metrics, question value calculus, answer readiness , and verification gates.
80 other projects use a version of this.
Adopted by
Most recently taken up by
- PeanutGT/NutsSkillstheir own version, first seen Nov 8, 2026
- venhdev/skillstheir own version, first seen Nov 8, 2026
- mel0nyrame/skillstheir own version, first seen Nov 8, 2026
- Integralist/agent-skillstheir own version, first seen Nov 6, 2026
- theexperiencecompany/gaiatheir own version, first seen Nov 3, 2026
- mag123c/toktracktheir own version, first seen Nov 3, 2026
Used with
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Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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owshq-mecSkilllayout
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- +8 more from HK-hub
Other versions80 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 80
- spool-lab/spool★ 592same name
- paperboytm/spool★ 590same name
- talesofai/cohub★ 585same name
- zaxbysauce/opencode-swarm★ 519same name
- ZaxbyHub/opencode-swarm★ 518same name
- educlopez/ui-craft★ 441same name
- nexmoe/DayBee★ 424same name
- nexmoe/eve★ 424same name
- ryanthedev/code-foundations★ 381same name
- Southclaws/storyden★ 348same name
70 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository28 other files it gives its agents.
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- copy-engineerSkill
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- anchorSkill
- boundary-detectorSkill
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- contradictSkill
- deep-thinkSkill
- descendSkill
- divergeSkill
- emergenceSkill
- excavateSkill
- fidelitySkill
- invertSkill
- meta-learningSkill
- negative-spaceSkill
- provenanceSkill
- reframeSkill
- shallowSkill
- teachSkill
- temporalSkill
- thresholdSkill
- verification-gatesSkill
- mobile-engineerSkill
- performance-engineerSkill
- product-engineerSkill
- refactor-engineerSkill
- system-architectSkill
The file
We split this skill into the rules it gives an agent
11 rules. 0 are common, 10 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 77 edited versions we read keep these.
10
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 36
Every prompt is either ready for an answer or missing something that would dramatically improve it.
- Distinctive: line 49
Ask a question the user already answered (implicitly or in prior context)
- Distinctive: line 73
Write your assessment of the incoming prompt:
- Distinctive: line 148
Write your final decision and reasoning:
- Distinctive: line 161
Artifact: Ask/Answer verdict.
- Very specific: line 298
If recursion_depth > 1, apply this entire protocol to your own output from Steps 1-4.
- Distinctive: line 301
Treat your previous output as the "answer under review"
- Distinctive: line 302
Run Steps 1-4 on it
- Distinctive: line 308
If RSM > 0.95 AND SI_d ≥ SI_{d-1} for 2 consecutive depths → CONVERGED, stop
- Distinctive: line 309
If RSM < 0.80 OR SI_d < SI_{d-1} for 2 consecutive depths → DIVERGED, stop, use best depth
- Distinctive: line 310
If d = max_depth → stop, use current
“Common” is measured: kept by at least 6 in 10 of the 77 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
CLARIFY v2.0 — Ask/Answer Decision Engine (Premium)
Mathematical Compliance: This skill implements the DEPTH-MATHEMATICS specification. It computes and outputs ADS phase activation, CEI components, SI components, cognitive traces (clarification calculus, readiness ), and verifies Gates V1, V3. It formalizes the ask/answer decision as a value calculus.
Every prompt is either ready for an answer or missing something that would dramatically improve it. You must decide: ask now, or answer now and refine later?
The wrong choice costs:
- Asking when you could answer: Wastes user's time, breaks flow, signals incompetence
- Answering when you should ask: Delivers wrong thing, requires revision cycles, erodes trust
This skill decides. Now it quantifies the decision.
The Failure Mode You Must Recognize
You are about to either:
- Ask a question the user already answered (implicitly or in prior context)
- Answer a question that will require 3 follow-up messages to converge
Both signal the same underlying failure: you assessed the prompt's information state incorrectly.
Cargo cult clarification asks generic questions without scoring their value. This skill rejects it.
The Protocol
0 — PARAMETERIZE: Read Thinking Parameters
Read thinking_parameters:
min_questions(default 1) — minimum questions to generate if askingvalue_threshold(default 3) — minimum total value score to askrequire_calculus(default true) — compute clarification calculusrequire_readiness_(default true) — issue answer readinessrecursion_depth(default 1) — recursive self-audit rounds
1 — ASSESS INTENT READINESS
Write your assessment of the incoming prompt:
INTENT ASSESSMENT
────────────────────────────────────────
Explicit request: [what user literally asked]
Inferred intent: [what they probably need - write one sentence]
Missing pieces: [what you don't know that would change the answer]
Confidence: [0-100% that you understand what they need]
Urgency signal: [does prompt contain "urgent", "asap", "right now"?]
Prior context: [relevant conversation history - yes/no]
Information State: [COMPLETE / PARTIAL / FRAGMENTED / UNKNOWN]
────────────────────────────────────────Artifact: Intent assessment.
CEI Component: Intent Assessment (weight 1.0)
2 — CLARIFICATION CALCULUS (if require_calculus = true)
NEW IN v2.0 — Formal value calculus for each potential question.
For each potential question, calculate its value:
QUESTION VALUE CALCULUS
────────────────────────────────────────
Question: [write the question]
Information Impact (II):
If I knew the answer, how much would my response change?
- Substantially (different approach): II = 2.0
- Moderately (refinement): II = 1.0
- Minimally (same answer either way): II = 0.0
User Cooperation Likelihood (UCL):
How likely will the user answer this?
- High (obvious gap, easy to answer): UCL = 1.0
- Medium (reasonable to ask): UCL = 0.5
- Low (intrusive, unclear): UCL = 0.0
Delay Cost (DC):
What is the delay cost?
- Low (quick answer): DC = 1.0
- Medium (some back-and-forth): DC = 0.5
- High (derails conversation): DC = 0.0
Prior Answer Probability (PAP):
How likely is the user to have already answered this implicitly?
- Low (genuinely unknown): PAP = 1.0
- Medium (might be in context): PAP = 0.5
- High (likely answered): PAP = 0.0
TOTAL VALUE = II × UCL × PAP + DC
[0.0 - 3.0]
Decision Threshold: [value_threshold, default 3.0 scaled]
If TOTAL VALUE ≥ threshold → ASK
If TOTAL VALUE < threshold → ANSWER (with caveats if 1-2)
────────────────────────────────────────Minimum min_questions questions evaluated.
Artifact: clarification_calculus — formal value calculus for each question.
CEI Component: Clarification Calculus (weight 3.0)
3 — DELIVER VERDICT
Write your final decision and reasoning:
ASK/ANSWER VERDICT
────────────────────────────────────────
Decision: [ASK / ANSWER / ANSWER-WITH-CAVEATS]
Primary question: [if asking - write it]
Reasoning: [2-3 sentences why this is the right call, referencing calculus]
What happens next: [if asking - wait for response]
[if answering - deliver and note what I'd ask if I could]
────────────────────────────────────────Artifact: Ask/Answer verdict.
CEI Component: Verdict (weight 1.0)
4 — ANSWER READINESS (if require_readiness_ = true)
NEW IN v2.0 — Formal of answer readiness.
ANSWER READINESS
────────────────────────────────────────
ID: arc_<timestamp>_<hash>
Prompt: [description]
Information State: [COMPLETE / PARTIAL / FRAGMENTED / UNKNOWN]
Questions Evaluated: [N]
Questions to Ask: [N]
Total Value Score: [0.0-3.0]
Threshold: [value_threshold]
Readiness: [READY / NOT_READY / CONDITIONAL]
If NOT_READY:
Missing Information: [list]
Questions to Ask: [list]
Expected Value Gain: [value]
If CONDITIONAL:
Caveats: [list]
Questions to Ask if Time Permits: [list]
Validity: [date or condition]
────────────────────────────────────────Artifact: readiness_ — formal verification of answer readiness.
CEI Component: Readiness (weight 2.0)
5 — METRICS: Compute and Output Depth Metrics
5.1 Phase Activation (for ADS)
{
"phase": 1,
"skill": "clarify",
"artifact_completeness": 0.XX,
"gate_pass_rate": 0.XX,
"external_validity": 0.XX,
"human_eval": 0.XX,
"phase_activation": 0.XX
}5.2 CEI Components
{
"cei_components": {
"intent_assessment": 1.0,
"clarification_calculus": 3.0,
"verdict": 1.0,
"readiness_": 2.0,
"total_complexity_weight": 7.0,
"output_tokens": N,
"wall_time_seconds": T,
"cei": 0.XX
}
}5.3 SI Components
{
"si_components": {
"c2_c3_count": 0,
"contrarian_viable": false,
"fatal_attacks": 0,
"boundary_violations": 0,
"assumption_reversals": 0,
"si_total": 0
}
}5.4 Cognitive Traces
Clarification Calculus:
{
"type": "clarification_calculus",
"questions": [
{"question": "...", "II": 2.0, "UCL": 1.0, "DC": 1.0, "PAP": 1.0, "total": 3.0, "decision": "ASK"},
{"question": "...", "II": 1.0, "UCL": 0.5, "DC": 0.5, "PAP": 0.5, "total": 0.625, "decision": "ANSWER"}
],
"threshold": 3.0,
"questions_to_ask": N
}Readiness : (as defined in Step 4)
5.5 Depth Contribution
{
"skill": "clarify",
"version": "2.0",
"metrics": {"ads_contribution": 0.XX, "cei": 0.XX, "si": 0, "ec": 0.XX},
"gates_verified": {"V1": true, "V3": true},
"limitations": ["..."]
}6 — GATES: Verify Before Delivery
MANDATORY — Verify these gates PASS:
| Gate | Check | Pass Condition |
| V1 | Assumption Coverage | Every missing piece in intent assessment traces to a question or caveat |
| V3 | Opposition Authenticity | If ANSWER: calculus shows why asking would be lower value |
If any gate FAILS: Return to relevant step and fix. Do not deliver.
7 — RECURSIVE SELF-AUDIT (if recursion_depth > 1)
If recursion_depth > 1, apply this entire protocol to your own output from Steps 1-4.
For each recursion level d = 2 to recursion_depth:
- Treat your previous output as the "answer under review"
- Run Steps 1-4 on it
- Compute RSM (Recursive Stability Metric):
RSM = 1 - Semantic_Distance(output_d, output_{d-1}) - Convergence Check:
- If RSM > 0.95 AND SI_d ≥ SI_{d-1} for 2 consecutive depths → CONVERGED, stop
- If RSM < 0.80 OR SI_d < SI_{d-1} for 2 consecutive depths → DIVERGED, stop, use best depth
- If d = max_depth → stop, use current
Artifact: recursion_log with RSM and SI at each depth.
CEI Component: Recursive Audit (weight 5.0 per level)
8 — INTERFERENCE: Receive and Provide
Receive from prior skills:
| From Skill | Interference | Use |
| BOUNDARY-DETECTOR | Knowledge gaps | Add as missing pieces in intent assessment |
| DEEP-THINK | Assumptions from restatement | Inform missing pieces |
| EXCAVATE | C2/C3 assumptions | Add as missing pieces |
Provide to later skills:
| To Skill | Interference | Minimum ADS Gain |
| DEEP-THINK | Missing pieces → assumption flags | +0.15 |
| EXCAVATE | Missing pieces → C2/C3 assumptions | +0.20 |
| CONDUCTOR | Readiness → skill selection | +0.15 |
| SHALLOW | Readiness → depth budget | +0.10 |
Artifact: interference_log (received and provided).
The Deeper Purpose
The model defaults to answering — it's what it's built to do. But sometimes the highest-value action is to slow down and ask. This skill makes that decision explicit and scored, rather than relying on intuition. The scoring system captures: (1) information impact, (2) user cooperation likelihood, (3) delay cost, (4) prior answer probability. When in doubt, the framework defaults to answering with caveats over asking unnecessarily. Now it's a formal calculus with s.
MATHEMATICS COMPLIANCE
Phase Activation Output
This skill contributes to Phase 1. It outputs:
{
"phase": 1,
"skill": "clarify",
"artifact_completeness": 0.XX,
"gate_pass_rate": 0.XX,
"external_validity": 0.XX,
"human_eval": 0.XX,
"phase_activation": 0.XX
}CEI Components
- Artifacts produced: intent_assessment (1.0), clarification_calculus (3.0), verdict (1.0), readiness_ (2.0)
- Total complexity weight: 7.0
SI Components
- C2/C3 assumptions: 0
- Contrarian viable: false
- Fatal attacks: 0
- Boundary violations: 0
- Assumption reversals: 0
Cognitive Traces Produced
- Clarification Calculus
- Readiness
- Decision Landscape
Gates Verified
- V1 [ ] V2 [x] V3 [ ] V4 [ ] V5 [ ] V6
- Human Eval [ ] Held-Out [ ] Ensemble
Required Interferences
- From BOUNDARY-DETECTOR: Knowledge gaps → missing pieces
- From DEEP-THINK: Assumptions → missing pieces
- From EXCAVATE: C2/C3 assumptions → missing pieces
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