agentleFS
AVANT-ICONICAVANT-ICONIC/skills/intent-mode/SKILL.md

intent-mode

Skill0 starsChanged 13 days agoMITView on GitHub

Reconstructs user intent from brain dumps, fuzzy requests, ambiguous goals, or solution-shaped prompts before planning, specification, or implementation.

1 other project uses a version of this.

Adopted by

Most recently taken up by

  • Other versions1 project uses a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 1

    1. AVANT-ICONIC/gpt-webui-skills★ 0same name

    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 repository11 other files it gives its agents.

The file

Show its rules and text

We split this skill into the rules it gives an agent

16 rules. About 0 are common, 16 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈16

    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:

    Do not use it merely because a request is short.

    line 23
  2. Distinctive:

    Do not implement product code while this skill is active.

    line 25
  3. Distinctive:

    Do not silently promote an inference into a requirement.

    line 64
  4. Distinctive:

    If a repository, document set, issue, specification, or other project source is available, inspect the relevant evidence before asking the …

    line 76
  5. Distinctive:

    Do not perform broad repository archaeology when a focused inspection answers the uncertainty.

    line 85
  6. Distinctive:

    Ask only questions whose answers could materially change:

    line 89
  7. Distinctive:

    Do not interview for ceremonial completeness.

    line 98
  8. Distinctive:

    When multiple questions are necessary, prefer independent questions before dependent ones.

    line 100
  9. Distinctive:

    If enough evidence already exists, ask nothing.

    line 102
  10. Distinctive:

    Prefer outcomes such as:

    line 108
  11. Distinctive:

    Avoid success criteria that merely restate implementation steps.

    line 115
  12. Distinctive:

    Before handoff, challenge the reconstructed intent.

    line 131
  13. Distinctive:

    Do not invent disagreement for appearance's sake.

    line 144
  14. Distinctive:

    Do not create or modify repository files unless the user requested persistent project changes or the active workflow already designates a …

    line 176
  15. Distinctive:

    If persistence is requested, update the existing source of truth instead of creating a competing document.

    line 178
  16. Distinctive:

    only genuinely material open decisions remain.

    line 198

≈ “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

Intent Mode

Reconstruct the real objective before solving it.

This skill is for rich but messy input: brain dumps, half-formed ideas, contradictory constraints, premature solution choices, scattered examples, or requests where the literal prompt may not yet describe the real problem.

The goal is not to make prompts prettier. The goal is to reduce semantic drift.

Use this skill when

  • the user provides a long brain dump;
  • the request is ambiguous or internally inconsistent;
  • the user proposes a solution but the underlying outcome is still unclear;
  • important constraints are implied rather than stated;
  • previous attempts or examples carry material context;
  • planning or specification would otherwise start from an unstable interpretation.

Do not use it merely because a request is short.

Do not implement product code while this skill is active.

Operating model

raw context
  ↓
reconstruct intent
  ↓
separate facts / inferences / unknowns / contradictions
  ↓
resolve only material gaps
  ↓
define observable success
  ↓
stress-test interpretation
  ↓
handoff

1. Reconstruct, do not summarize

A summary compresses what the user said.

Intent reconstruction identifies what the user is trying to achieve.

Build an explicit model of:

  • Objective — the outcome that matters;
  • Motivation — the friction, opportunity, or failure being addressed;
  • Actors — who uses, operates, or is affected by the result;
  • Constraints — conditions that must remain true;
  • Success criteria — observable evidence of success;
  • Non-goals — things intentionally outside the target;
  • Assumptions — unverified beliefs filling missing context;
  • Contradictions — statements that cannot all be satisfied simultaneously;
  • Open decisions — choices requiring user judgment;
  • Proposed solution — the current implementation idea, when one exists.

Do not silently promote an inference into a requirement.

When useful, distinguish:

desired outcome ≠ current proposed solution

The proposed solution may still be correct. It simply must not hide the actual objective.

2. Inspect available evidence

If a repository, document set, issue, specification, or other project source is available, inspect the relevant evidence before asking the user factual questions.

Use:

retrievable fact → inspect
preference / intent → ask

Do not perform broad repository archaeology when a focused inspection answers the uncertainty.

3. Resolve only material gaps

Ask only questions whose answers could materially change:

  • scope;
  • behavior;
  • architecture;
  • acceptance criteria;
  • risk;
  • cost or implementation strategy.

Do not interview for ceremonial completeness.

When multiple questions are necessary, prefer independent questions before dependent ones.

If enough evidence already exists, ask nothing.

4. Define the finish line

Translate the reconstructed objective into observable success criteria.

Prefer outcomes such as:

WHEN <relevant condition>
THEN <observable result>

Avoid success criteria that merely restate implementation steps.

Bad:

Add a scheduling database.

Better:

Two users cannot successfully reserve the same slot.

5. Stress-test the interpretation

Before handoff, challenge the reconstructed intent.

Check:

  • the strongest plausible alternative interpretation;
  • the assumption with the largest downside if wrong;
  • whether a stated constraint is actually a preference;
  • whether the success criteria measure the desired outcome;
  • whether a previous failed approach has leaked into the requirements;
  • whether the proposed solution is unnecessarily constraining the problem.

Report only material weaknesses.

Do not invent disagreement for appearance's sake.

6. Produce an Intent Brief

The primary output is a compact, inspectable Intent Brief:

# Intent Brief

## Objective

## Motivation

## Actors

## Constraints

## Success criteria

## Non-goals

## Assumptions

## Contradictions

## Open decisions

## Proposed solution

Omit empty sections when that improves clarity.

Do not create or modify repository files unless the user requested persistent project changes or the active workflow already designates a planning artifact as writable.

If persistence is requested, update the existing source of truth instead of creating a competing document.

Handoff

Route the result based on remaining uncertainty.

  • Planning: material product, scope, architecture, workflow, or tradeoff decisions remain.
  • Specification: intent and important decisions are already settled.
  • Direct execution: the task is small, clear, and does not need a separate planning/specification stage.

The next agent or skill must inherit the Intent Brief rather than reconstructing the original request from scratch.

Completion criteria

Intent Mode is complete when:

  • the underlying objective is explicit;
  • the solution is separated from the outcome where relevant;
  • constraints, non-goals, assumptions, and contradictions are visible;
  • success criteria are observable;
  • only genuinely material open decisions remain;
  • downstream work can proceed without reinterpreting the user's original input.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.