agentleFS
ConnorGriffinConnorGriffin/follow-through/AGENTS.md

follow-through

AGENTS.md0 starsChanged 3 months agoMITView on GitHub

Public Agent Skill and repository template for durable personal memory, ADR-style decisions, plans, reviews, and outcomes. profile: reviewed - Never copy personal records or Git history from a private repository into this project. - Never use real personal records as examples or test fixtures. Create explicitly labeled synthetic records. - Never weaken or bypass scripts/privacy_check.py to make a finding pass. - Never make bootstrap create a remote or push a user's private repository. - Never apply a schema update without…

  • Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.

    Of the AGENTS.md files we read, the 31,700 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.

  • In this repository3 other files it gives its agents.

The file

We split this AGENTS.md into the rules it gives an agent

7 rules. About 0 are common, 5 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Check publication boundary: python3 scripts/privacy_check.py

    line 13
  2. Distinctive:

    Never copy personal records or Git history from a private repository into this project.

    line 21
  3. Distinctive:

    Never use real personal records as examples or test fixtures.

    line 23
  4. Very specific:

    Never weaken or bypass scripts/privacy_check.py to make a finding pass.

    line 25
  5. Distinctive:

    Never make bootstrap create a remote or push a user's private repository.

    line 26
  6. Distinctive:

    Never apply a schema update without first presenting its diff for explicit approval.

    line 27
  7. Distinctive:

    Keep runtime code on the Python standard library unless a dependency is genuinely unavoidable and approved.

    line 29

≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md 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
AGENTS.md

Follow Through

Public Agent Skill and repository template for durable personal memory, ADR-style decisions, plans, reviews, and outcomes.

profile: reviewed

Repo facts

  • Install: none.
  • Test: python3 -m unittest discover -s tests -v
  • Validate example: python3 scripts/validate.py examples/maya-chen
  • Check publication boundary: python3 scripts/privacy_check.py
  • Development server: none.
  • Skill and implementation: SKILL.md, references/, scripts/, assets/
  • Tests: tests/
  • Synthetic fixture: examples/maya-chen/

Hazards

  • Never copy personal records or Git history from a private repository into this project.
  • Never use real personal records as examples or test fixtures. Create explicitly labeled synthetic records.
  • Never weaken or bypass scripts/privacy_check.py to make a finding pass.
  • Never make bootstrap create a remote or push a user's private repository.
  • Never apply a schema update without first presenting its diff for explicit approval.
  • Keep runtime code on the Python standard library unless a dependency is genuinely unavoidable and approved.
  • Preserve the two-commit synthetic lifecycle: its Git history is validator coverage for awaiting-outcome to reviewed.

ui-surfaces: none

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.