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/chisel

@965f4f9
by shingo imotasimota/agent-skills85 stars
15

Converting a supplied prompt into an executable specification: detects vague quality/quantity/explanation/style/design/technical/judgment wording, role and persona theater, and self-contradiction, then replaces each with a numeric bound, an observable behavior, or a scorable criterion — with a per-term ledger of what changed and what stayed open. Don't use for AI system design, RAG, or eval harnesses (Oracle), PRD/SRS authoring (Scribe), spec conformance verification (Attest), or SKILL.md normalization (Gauge).

Use this Skill: https://skilld.dev/gh/simota/agent-skills/chisel

This session only. Nothing lands on disk.

referenceambiguity-budget.md

≈1.7k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Ambiguity Budget

Purpose: Deciding what to leave unspecified, proving each added line earns its place, and scoring the Exit Checklist. Read when: You are in CLASSIFY deciding on a KEEP, in RECONCILE running the delete test, or the audit Recipe is active.

Contents

  • The premise
  • The KEEP test
  • Where ambiguity is load-bearing
  • The delete test
  • Requirements a prompt cannot hold
  • Over-specification failure modes
  • Exit Checklist scoring

The Premise

"Eliminate every vague term" is not the goal, and pursued literally it produces a worse prompt. Specification has a cost: each fixed rule removes a decision the executor could have made better with the material in front of it, and each added line competes for attention with the lines that matter.

The goal is that every ambiguity is either resolved or deliberate. An unexplained vague term is a defect. So is a term specified when it should have been delegated. The ledger makes the difference visible.


The KEEP Test

KEEP requires all three to hold. If any fails, translate it.

  1. The executor has better information than the author did. The right choice depends on material the executor will see and the author could not anticipate.
  2. The choice is reversible. A wrong pick costs a revision, not a wasted deliverable.
  3. A guess would narrow the space unhelpfully. Fixing it early forecloses options that are the point of the task.

Every KEEP row records which of these applied. "Left vague" with no reason is indistinguishable from an oversight, and a later reader will remove it.


Where Ambiguity Is Load-Bearing

Situation Why specifying hurts
Exploration and ideation Fixing the output shape makes the executor fill blanks instead of finding what matters. Formalize after the content settles, not before
Wording, naming, section order Reversible surface choices the executor makes better in context; pinning them adds lines and removes nothing
Candidate generation A stated count or format biases toward filling the quota rather than toward quality
Approach selection on an unsolved problem Prescribing the method pre-commits to the author's guess about a solution they do not have
Process whose order carries no correctness A fixed sequence with no safety, correctness, or auditability rationale is over-specified process (_common/architect/reference/official-design-patterns.md § Process Constraint Tiers)

The inverse also holds: order is worth fixing when the sequence itself carries correctness, safety, or auditability — measure before optimizing, reproduce before fixing, snapshot before mutating.


The Delete Test

Every line added to the rewritten prompt must pass: remove it, and would the output plausibly differ? If not, it does not ship.

Common failures:

  • A rule restating what the model already does by default.
  • A rule already implied by a stronger rule three lines above.
  • A quality criterion no reader could check.
  • A prohibition against a failure the task cannot produce.

This is the same admission rule the ecosystem applies to its own instructions (_common/MECHANISM_SELECTION.md § Admission). A specified prompt is frequently shorter than its source, because decorative role text and duplicated rules are removed. Net growth without a per-line justification means over-specification crept in.


Requirements a Prompt Cannot Hold

Some detections should not be translated into stronger wording at all, because no wording enforces them. Name the enforcing layer instead and route it.

Requirement Prompt-only failure Enforcing layer
Always valid structured output Stray prose, missing key, wrong type Schema validation plus retry
Never exceed a spend or usage cap Misread, or overridden by injected text Code-side check before the call
Never touch secrets or out-of-scope data Complies in wording, reads anyway Tool permission, secret isolation
Facts are current Recall beyond the cutoff, missed retrieval Retrieval plus source-date check
Irreversible action requires approval Wording ignored under ambiguity Approval gate outside the prompt

Full classification — MUST SPECIFY / SHOULD SPECIFY / CONDITIONAL / DELEGATE / DO NOT RELY ON PROMPT — lives in oracle/reference/prompt-engineering.md § Instruction Boundary. Chisel consumes that classification; it does not restate it.

Before rewriting at all, confirm the prompt is the problem. When the complaint is a bad output, run the five-layer triage in the same file (Instruction / Context / Capability / Tool / Evaluation) — retrieval failures and evaluator failures are routinely misdiagnosed as prompt failures, and rewriting wording fixes neither.


Over-Specification Failure Modes

Mode Symptom Cost
Premature formatting A schema or section list fixed during an exploratory task Discovery drops; the executor fills blanks
Process pinning A step order stated where order carries no correctness Blocks better paths for no safety gain
Criterion inflation Twelve quality criteria for a two-paragraph answer Attention spreads; none is enforced
Variable sprawl Six or more {{VARIABLE}} placeholders The prompt becomes a form and gets abandoned
Redundant restatement The same rule in Execution rules and Quality checks Signals the author does not trust the first statement; both get skimmed

Exit Checklist Scoring

Used by the audit Recipe and before every EMIT. Score each item pass or fail with the offending line cited.

# Item Fails when
1 No vague-for-vague substitution A translated rule contains a term from the lexicon with no bound, behavior, or criterion attached
2 Roles became capabilities A bare title, seniority claim, or credential survives
3 Discretion words resolved An "as appropriate" remains without either both branches or a recorded KEEP
4 Numbers are licensed A figure appears that traces to neither source text, a labeled estimate, nor a variable
5 Conflicts handled Two rules collide with no merge, no stated precedence, and no ledger entry
6 No duplication; delete test passed A rule appears twice, or a line's removal would change nothing
7 Intent preserved A goal, audience, or constraint appears that is not in the source, or one from the source is missing
8 Third-party checkable A reader who never saw the original could not score the output pass or fail

Any failure blocks delivery. For audit, return the failing items with the minimal patch for each — not a rewritten prompt, which is the spec Recipe's deliverable.

Source: SKILL.md on GitHub

No alerts13d3 checks · Risk SAFE
  • Gen Agent Trust Hub13d

    The skill is a prompt engineering assistant designed to detect and resolve ambiguity in user instructions. It transforms vague language into explicit, executable specifications through a structured workflow. The analysis found no evidence of malicious patterns, data exfiltration, or unauthorized command execution. The skill correctly identifies its own logical boundaries by routing technical requirements like security protocols and spend caps to appropriate enforcing layers rather than relying on prompt-layer hardening alone.

  • Socket13d

    No alerts

  • Snyk13d

    Risk: LOW · No issues

Signed by skilld at 965f4f9. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 days ago.

Activeupdated 2 weeks ago

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