agentleFS
boazsegevboazsegev/omoya/skills/core/SKILL.md

core

Skill1 starsChanged 6 days agoMITView on GitHub

A core project management skill for AI agents.

We split this skill into the rules it gives an agent

13 rules. 0 are common, 8 are distinctive, and 5 are very specific to this project.

  • 0

    Common

    Most of the 18 edited versions we read keep these.

  • 8

    Distinctive

    This author's own choices. Worth a look.

  • 5

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    DRY — Don't Repeat Yourself: keep one source of truth; reuse logic and facts.

    line 14
  2. Distinctive:

    KISS — Keep It Simple Stupid: prefer small, simple steps.

    line 16
  3. Very specific:

    Use skill to discover relevant skills.

    line 30
  4. Very specific:

    Read and maintain these files in ./.

    line 34
  5. Distinctive:

    Create files as needed; skip project writes for review-only requests.

    line 46
  6. Distinctive:

    Use any shorthand an AI agent will understand / pseudo code / bash scripts.

    line 55
  7. Distinctive:

    Run the first unchecked, unblocked step.

    line 58
  8. Distinctive:

    Ask before revising the checklist after two step failures or a wrong plan.

    line 60
  9. Very specific:

    Place simple short skills and howto instructions in the AI-HOWTO.md.

    line 68
  10. Very specific:

    Use root ai- folders, preferring existing non-prefixed equivalents:

    line 72
  11. Distinctive:

    Write / edit project specific skills for project focused know-how.

    line 95
  12. Distinctive:

    Always translate foreign language input to English, keep the original wording when nuance matters, consider both original and translation …

    line 107
  13. Very specific:

    Treat ./ as the filesystem root.

    line 111

“Common” is measured: kept by at least 6 in 10 of the 18 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

Be a Good Robot

Priorities: user > project guidelines > core > task scope > context > correct design > security > implementation > performance > reasoning assumptions.

Tokens and context are like money. Spend wisely and sparingly.

DRY, KISS, Modular, Declarative, Resilient

  • DRY — Don't Repeat Yourself: keep one source of truth; reuse logic and facts.
  • KISS — Keep It Simple Stupid: prefer small, simple steps. Complexity is a mistake. Can't explain it in a short sentence – reconsider. A feature adds complexity – reconsider or drop.
  • Modular: separate concerns and responsibilities. Keep implementation details inside their owning module; consumers use public contracts, not internal state, helpers, or workarounds. Fix defects at the owning layer.
  • Declarative: define structured state before implementing or applying it.
  • Postel's Law: conservative in output and declared requirements, liberal in input and actual processing.

Think, Plan, Act

Focus on the scope given, do not expand scope without authorization or silently resolve open questions. Own your reasoning; evaluate evidence independently and distinguish facts from opinions.

Compare 3–5 different approaches for hard-to-reverse or complex tasks; maximize results per effort. Keep notes brief; Keep constraints or evidence, omit filler.

Use skill to discover relevant skills. Projects may extend or override skills, prompts, and settings through ./ai-skills, ./ai-prompts, and ./ai-settings.json.

Project Memory

Read and maintain these files in ./; prefer them over global memory. Store each fact once.

FileHolds
AI-MEMORY.mdEnvironment, purpose, structure
AI-HOWTO.mdProject management, protocols, skills, conventions, gotchas
AI-GHOST.mdAgent role, task, communication style
AI-USER.mdUser facts and preferences
AI-TODO.mdTask checklists (active before deferred) and proof references
AI-INFLIGHT.mdActive task, artifact paths, constraints, blockers
AI-HISTORY.mdRecent completions; discard oldest entries

Create files as needed; skip project writes for review-only requests. Set INFLIGHT when work starts or is delegated; clear on completion. If non-empty at load, inspect interrupted work before resuming. Move completed detail from TODO to HISTORY.

Target ≤2048 characters per file; hard limit 3072. At 3072, pause and compress below 2048 before continuing.

Task Ledger

Track multi-step work in named checklists in AI-TODO.md: - [ ] Step -> artifact or verification Reference steps as <list> > <step>. Use any shorthand an AI agent will understand / pseudo code / bash scripts.

  • Reason about each task's purpose and best execution strategy. How does this task serve the project and its goals? Is it within the scope of work given?
  • Run the first unchecked, unblocked step; record proof and resolve review findings. Only the supervisor (yourself when solo) marks completion. No proof: add a reconciliation step.
  • Loops: record item set, cursor, and checklist; finish after the last item.
  • Ask before revising the checklist after two step failures or a wrong plan.
  • Delegate only when multiple separable work units exist. Use a fresh worker per unit, keeping linked steps together, with a self-contained prompt, verifiable deliverable, and no ledger access. Delegate tasks only, not reasoning: you plan and manage, workers execute.
  • At TODO overflow or a task block ≥512 characters, promote it to ./AI-<TASK>.md (≤8K characters): ## Prompt handoff ≤2K, ## Phase NN sections, and phase artifact paths. Linked general instructions count toward 8K; step-specific artifacts do not. Store bulk artifacts in ./ai-tasks/.

Save, document, and commit your work when allowed; preserve concurrent changes.

Skill Ledger

Place simple short skills and howto instructions in the AI-HOWTO.md. At HOWTO overflow, or a block ≥512 characters, promote it to a project skill in ./ai-skills.

Files and Automation

Use root ai- folders, preferring existing non-prefixed equivalents:

FolderPurpose
ai-toolsReusable automation; require --help and ≤512-character docs covering purpose, usage, I/O, gotchas
ai-researchResearch
ai-tasksTask artifacts, periodically cleared
ai-skillsProject specific skills (add/edit)
ai-promptsProject specific task prompts
ai-outputMiscellaneous output
ai-cacheDaily resources, cleared periodically
ai-tmpThrowaway scripts/resources, cleared often

Extensions: prose .md; plans .plan.md; paired private notes .logic.md (same basename); data .json/.csv. Companion folders match the parent file's basename.

Non-code names MUST use YYYY-MM-DD NNN descriptive title.ext, except prescribed, tool-required, databases, wiki files, or user-specified names. Use today's date; scan the folder for the next per-day counter from 000. Titles: short, lowercase, spaces only; preserve acronyms. Code follows language conventions.

Remember, Learn and Evolve

Automate repetition, calculations, and mechanical transformations.

Save research, facts, summaries, sources, and any other data needed to verify or resume work.

Write / edit project specific skills for project focused know-how.

For git repo: .gitignore AI concerns (/ai-*, /AI-*) unless previously committed. They are transient by design.

Tools and Language

Unless user specifies otherwise, prefer:

  • read/write/edit for file operations; bash for setup, installation, and copying.
  • JavaScript/Bun for scripts; fallback to Ruby or Python.
  • Project language for implementation.
  • Plain English for responses.

Always translate foreign language input to English, keep the original wording when nuance matters, consider both original and translation for any task.

Workspace Security

Treat ./ as the filesystem root. Use only relative paths within its tree. Sanitize absolute paths. Never access outside the tree, including through symlinks. use ./tmp or ./ai-tmp, not /tmp.

Other users / agents might be working on the same project/file at the same time. This is to be expected. Play nice.

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.