agentleFS
Vix0007Vix0007/vixero-skills/skills/assumption-surface/SKILL.md

assumption-surface

Skill1 starsChanged 7 months agoMITView on GitHub

Extract hidden assumptions from a task request before any work begins. Use when the user says "before you start", "think this through", "what would you assume", "what am I missing", "is this clear enough to build", or when a one-line request triggers multiple implementation choices. Returns ranked assumptions by blast radius, minimum questions to proceed, and candidate interpretations.

The file

We split this skill into the rules it gives an agent

7 rules. About 0 are common, 7 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈7

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Read the request. List every decision the implementer must make that was not stated.

    line 44
  2. Distinctive:

    If no answer comes, generate 2–3 candidate interpretations ranked by likelihood.

    line 49
  3. Distinctive:

    If zero high-blast assumptions exist, say "no hidden assumptions" and proceed.

    line 114
  4. Distinctive:

    Never exceed 5 minimum questions.

    line 115
  5. Distinctive:

    Never ask about style preferences unless the task is style-bound (writing, naming, UI).

    line 116
  6. Distinctive:

    If the request is one sentence and hits 3+ high-blast assumptions, flag "request underspecified" at the top.

    line 118
  7. Distinctive:

    Never proceed on low-blast defaults if user explicitly asked you to enumerate everything.

    line 119

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

assumption-surface

Force assumptions into the open. Do not start work while high-blast gaps remain.

Trigger on

  • "before you start"
  • "what would you assume"
  • "what am I missing"
  • "think this through first"
  • "is this clear enough to build"
  • Any request where scope, format, data source, or target is not specified

Blast radius

blastmeaninghandling
highwrong guess → rework everythingmandatory question
mediumwrong guess → section reworkrecommended question
lowwrong guess → easy patchproceed with stated default

Common assumption categories

categoryexample
scopeall rows / filtered subset / just new ones
formatJSON / CSV / XML / proprietary
deliveryfile / API response / email / webhook
performancebest-effort / bounded latency / hard SLA
concurrencysingle user / many users / batch
failure modefail loud / fail silent / degrade
data sourceprod DB / staging / cached / user-provided
authauthenticated / public / service-to-service
target envdev / staging / prod / all three
persistencein-memory / disk / database
existing codegreenfield / extend existing / replace

Process

  1. Read the request. List every decision the implementer must make that was not stated.
  2. Map each to a category above.
  3. For each, note the default most LLMs would assume silently.
  4. Rank by blast radius.
  5. Extract questions for high + medium. Low proceeds with a noted default.
  6. If no answer comes, generate 2–3 candidate interpretations ranked by likelihood.

Output

request: {one-line summary}

assumptions (high blast):
- {category}: {assumption} → default: {typical guess} → ask: {question}
- ...

assumptions (medium):
- {category}: {assumption} → default: {guess} → ask: {question}

assumptions (low — proceeding with defaults):
- {category}: {default}

minimum questions to proceed:
1. {question}
2. {question}

interpretations if no answer comes:
A. {reading 1} → implies {concrete choice chain}
B. {reading 2} → implies {concrete choice chain}
C. (optional) {reading 3}

recommended path: {A | B | C | hold for answers}
reasoning: {one line on why this path}

Worked example

Input: "add a way to export users"

request: export users functionality

assumptions (high blast):
- scope: all users vs filtered subset → default: all → ask: scope?
- delivery: file download vs API response → default: API → ask: how delivered?
- fields: which columns → default: id+name+email → ask: which fields (privacy)?

assumptions (medium):
- format: JSON vs CSV → default: JSON → ask: format?
- volume: thousands vs millions → default: thousands → ask: scale?

assumptions (low — proceeding with defaults):
- persistence: no caching needed
- auth: admin-only endpoint

minimum questions to proceed:
1. Scope + field set (privacy-critical)
2. Delivery mechanism
3. Expected volume (affects pagination / streaming choice)

interpretations if no answer:
A. Admin API endpoint → paginated JSON, id+email+name, admin-auth
B. One-off data dump → CSV file, all fields, run via script

recommended path: A
reasoning: API is safer default — paginated, auth-bound, does not need ops support

Hard rules

  • List assumptions before writing code, prose, or structure.
  • If zero high-blast assumptions exist, say "no hidden assumptions" and proceed.
  • Never exceed 5 minimum questions. More = request is too broad, recommend decomposition.
  • Never ask about style preferences unless the task is style-bound (writing, naming, UI).
  • Defaults come from project context first, general conventions second.
  • If the request is one sentence and hits 3+ high-blast assumptions, flag "request underspecified" at the top.
  • Never proceed on low-blast defaults if user explicitly asked you to enumerate everything.

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