agentleFS
anxndsgnanxndsgn/skills/to-spec/SKILL.md

to-spec

Skill1 starsChanged 51 days agoApache-2.0View on GitHub

Turn the current conversation into a spec — no interview, just synthesis of what you've already discussed.

194 other projects use a version of this, 149 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use setup-ts-deep-modules, to-questionnaire and 10 more.

Other files people use alongside this one.

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.
  • liufeng1976Skill

    setup-ts-deep-modules

    Wire dependency-cruiser into a TypeScript repo so each package is a deep module — implementation hidden in subfolders, reachable only through its entry-point files. User-invoked.

    Also in 43 projects that use this

  • AWSSkill

    to-questionnaire

    Turn a decision you can't fully answer into a questionnaire for someone else to fill in.

    Also in 90 projects that use this

  • RoentekSkill

    loop-me

    Grill me about specs for the workflows I want to build, within this workspace.

    Also in 49 projects that use this

  • AWSSkill

    wizard

    Generate an interactive bash wizard that walks a human through steps only they can perform. Use when provisioning infrastructure, setting up credentials or CI secrets, walking an unfamiliar third-party dashboard, or running a one-off migration or cutover. Don't invoke this for steps the agent can perform itself.

    Also in 116 projects that use this

  • ryotaroh180105Skill

    claude-handoff

    Hand the current conversation off to a fresh background agent that picks up the work immediately.

    Also in 39 projects that use this

  • LesaniSkill

    writing-beats

    Shape an article as a journey of beats, choose-your-own-adventure style. The user picks a starting beat from the raw material, you write only that beat, then offer options for where to pivot next, beat by beat, until the article reaches a natural end. Use when the user has raw material and wants to assemble it as a narrative rather than an argument.

    Also in 51 projects that use this

  • +2 more from aws

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 182 edited versions we read keep these.

  • 2

    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
  1. Very specific:

    If the conversation holds no decisions to synthesize, say so and point to /grill-me instead of writing a spec from guesses.

    line 30
  2. Distinctive:

    Do not include specific file paths or code snippets.

    line 44
  3. Distinctive:

    Prefer existing test seams and external behavior.

    line 56

“Common” is measured: kept by at least 6 in 10 of the 182 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.

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

This skill takes the current conversation context and codebase understanding and produces a spec (you may know this document as a PRD). Do not interview the user; synthesize what the conversation already established.

Process

  1. Explore the repo to understand the current state of the codebase, if you haven't already. Use the project's established domain vocabulary throughout the spec, and respect any ADRs in the area you're touching. If the repo has an established spec home and house style (e.g. docs/spec/ with a frontmatter convention and normative prose), write the spec there in that style — adapt this template's sections to it rather than imposing the template's headings.
  2. Sketch out the seams at which you're going to test the feature. Existing seams should be preferred to new ones. Use the highest seam possible. If new seams are needed, propose them at the highest point you can. The fewer seams across the codebase, the better - the ideal number is one.
  3. Write the draft using established decisions and repository evidence. Record proposed test seams and unresolved choices explicitly; keep proposals distinct from agreed requirements. Ask a focused question only when missing information would materially change the solution, and complete the independent parts of the draft first. Routine test-seam choices do not require confirmation.
<spec-template>

Problem Statement

The problem that the user is facing, from the user's perspective.

Solution

The solution to the problem, from the user's perspective.

Behavioral Coverage

The decisions already exist earlier in the conversation. Do not restate them as user stories; post-hoc stories are decision projections, not requirements, and they add reading weight without adding constraint. Instead do the one thing the story exercise is genuinely good for: an actor × situation sweep for edges no decision has covered yet — empty states, missing configuration, offline, version skew, races, permission and auth failures, idempotent re-runs. Write the result as a numbered ### Acceptance Criteria subsection: externally observable behaviors a test could assert. Add a story only when it pins down behavior nothing else has fixed.

If the conversation holds no decisions to synthesize, say so and point to /grill-me instead of writing a spec from guesses.

Implementation Decisions

A list of implementation decisions that were made. This can include:

  • The modules that will be built/modified
  • The interfaces of those modules that will be modified
  • Technical clarifications from the developer
  • Architectural decisions
  • Schema changes
  • API contracts
  • Specific interactions

Do not include specific file paths or code snippets; they go stale quickly.

Exception: if a prototype produced a snippet that encodes a decision more precisely than prose can (state machine, reducer, schema, type shape), inline it within the relevant decision and note briefly that it came from a prototype. Trim to the decision-rich parts — not a working demo, just the important bits.

Verification Plan

For each acceptance criterion, name the smallest credible evidence that would prove it. Include:

  • Relevant tests or other checks
  • Runtime or manual verification where automation is insufficient
  • Applicable typecheck, lint, build, migration, or compatibility checks

Prefer existing test seams and external behavior. Do not invent exact commands or file names that the repository has not confirmed.

Out of Scope

A description of the things that are out of scope for this spec.

Further Notes

Any further notes about the feature.

</spec-template>

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.