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agent-friction-ledger

Skill16 starsChanged 5 months agoMITView on GitHub

Capture recurring agent-development friction as a local, privacy-safe Markdown report. Use only when the user explicitly requests a friction review of blockers, misleading errors, missing documentation, incompatible tools, or manual workarounds that should improve a doc, tool, skill, process, or evaluation.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 5 are distinctive, and 1 is 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.

  • 1

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Do not run merely because a task had normal shell output, a single failed command, or a clean completion.

    line 20
  2. Distinctive:

    Do not record every tool call, full conversation, raw logs, private URLs, credentials, personal data, client data, or unrelated …

    line 32
  3. Very specific:

    Write a local report to an ignored or private location only.

    line 40
  4. Distinctive:

    Never write to a tracked repo path by default.

    line 71
  5. Distinctive:

    Prefer one concise report over a growing per-turn buffer.

    line 73
  6. Distinctive:

    If the task contains regulated, personal, client, deal, financial, or credential data, record the abstract failure mode only.

    line 74

≈ “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

Agent Friction Ledger

Turn repeatable agent friction into a small, actionable local artifact. This skill is opt-in and never sends session data outside the workspace.

Trigger

Use only when:

  • the user explicitly asks for a friction report or review.

Do not run merely because a task had normal shell output, a single failed command, or a clean completion.

Capture Rules

Record only friction that is actionable and evidenced by the current task:

  • repeated blocker or retry loop;
  • misleading, incomplete, or contradictory error;
  • missing, stale, or hard-to-find documentation;
  • tool, provider, environment, or version incompatibility;
  • manual workaround that should become a durable improvement.

Do not record every tool call, full conversation, raw logs, private URLs, credentials, personal data, client data, or unrelated working-tree changes.

Workflow

  1. Name the task boundary and identify only the material friction events.
  2. For each event, record: symptom -> attempted -> root cause -> resolution -> durable fix.
  3. Mark confidence: confirmed, likely, or unresolved. Do not turn a guess into a root cause.
  4. Redact or omit sensitive content before writing.
  5. Write a local report to an ignored or private location only. Default to .git/agent-friction/YYYY-MM-DD-<task>.md unless the repo defines another approved ignored path.
  6. Group action items under docs, tooling, skill/process, and research.
  7. Propose the smallest durable change, but do not apply it without normal task authorization.

Report Shape

# Agent Friction Report: <task>

## Scope
## Material Friction
### <short label>
- Symptom:
- Attempted:
- Root cause: <confirmed|likely|unresolved>
- Resolution:
- Durable fix:

## Action Items
### Docs
### Tooling
### Skill / Process
### Research

## Decision
- Keep local / propose follow-up / no durable change

Guardrails

  • Local Markdown only. Never POST to a viewer, telemetry endpoint, or external API.
  • Never write to a tracked repo path by default. If no ignored/private location exists, stop and ask before writing.
  • A friction report is not permission to create a ticket, alter a skill, edit docs, or change a process.
  • Prefer one concise report over a growing per-turn buffer.
  • If the task contains regulated, personal, client, deal, financial, or credential data, record the abstract failure mode only.

Pair With

  • repo-debugging-ledger for hypothesis-driven technical diagnosis;
  • durable-context-maintenance when an accepted fix belongs in repo context;
  • token-usage-audit when the friction is context or tool-output waste;
  • skillopt-evolve-skills and bounded-evaluation when an accepted skill change needs validation.

Provenance

Adapted from aurorascharff/agent-friction-skill, narrowed to explicit, local-only, privacy-safe friction capture with proposal-gated follow-up.

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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.