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RonnasaydRonnasayd/aipp/skills/everything-claude-code/agent-introspection-debugging/SKILL.md

agent-introspection-debugging

Skill1 starsChanged 33 days agoNo licenceView on GitHub

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

23 other projects use a version of this, 20 of them edited.

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Used with

Projects with it also use unified-memory, brand-discovery and 5 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.
  • gongyijie85Skill

    unified-memory

    Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer context, resume another agent's task, or search shared project knowledge.

    Also in 3 projects that use this

  • ysyecustSkill

    brand-discovery

    Use when a brand needs to discover or articulate its identity through structured multi-session interviews. Covers purpose, positioning, audience, personality, voice, narrative, and founder-brand tension across 8 modules using laddering, 5 Whys, and projective techniques. Produces a resumable session with disk-persisted state and a master brandbook (90_SYNTHESIS.md).

    Also in 3 projects that use this

  • ysyecustSkill

    competitive-platform-analysis

    Use when scoping a competitive landscape — identifying, categorising, and score-filtering a competitor set before any benchmarking begins. Decides who counts as a competitor, which tier they belong to, and which sources to mine. First step in the three-skill competitive pipeline; precedes benchmark-methodology.

    Also in 3 projects that use this

  • mturacSkill

    mle-workflow

    Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.

    Also in 4 projects that use this

  • InfopibeSkill

    everything-claude-code

    Also in 3 projects that use this

  • +2 more from ysyecust

The file

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14 rules. 10 are common, 0 are distinctive, and 4 are very specific to this project.

  • 10

    Common

    Most of the 20 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 4

    Very specific

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

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 20 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.

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