smithery.ai

aep

Experimental v1.0 of Robi AEP with richer schema (1.0-exp), better pack matching, confidence scoring, and pack evolution metadata. Still repo-native and file-based; use when you want more expressive, experimental AEP behavior on top of the stable v0.1 design.

First seen Mar 31, 2026

Installation

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Declared
Codex Declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Declared
Cline Not declared
OpenCode Declared

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code cursor codex gemini opencode

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 7,646 B
  • docs SUMMARY.md 270 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 5 installs

SKILL.md

Robi AEP Skill v1.0-exp

This is an experimental extension of the Robi AEP Skill.

Core idea remains the same:

  • Convert successful collaborations into Agent Experience Packs (AEPs) stored in the active agent's directory.
  • Use those packs to align future tasks.

v1.0-exp adds:

  • richer matching metadata (applies_to, strength)
  • metrics and history for how packs evolve
  • optional merge suggestions between overlapping packs

Everything is still repo-local and file-only.


Agent-Aware Install Target (Required)

Do not default to .agent/ in v1.0-exp.

When creating or updating AEP files, first detect which agent environment is active for the repo, then install into that agent's directory.

Preferred targets:

  • Claude: .claude/aep/
  • Codex: .codex/aep/
  • Gemini: .gemini/aep/
  • OpenCode: .opencode/aep/
  • Cursor: .cursor/aep/

If multiple agent directories exist, choose in this order:

  1. directory explicitly referenced by the user
  2. directory that already contains aep/ files
  3. directory matching the currently used agent
  4. ask the user if still ambiguous

Do not create .agent/ for new installs.

Instruction file updates (Required after save/create)

After creating an AEP pack (or initializing AEP in a repo), update agent instruction files so future sessions know to use AEP by default.

Update/create these when present or relevant:

  • AGENTS.md
  • CLAUDE.md
  • Codex instructions file (for the repo's Codex setup)
  • Gemini instructions file (for the repo's Gemini setup)
  • OpenCode agent instruction/config file
  • Cursor project instruction/rules file

Minimum instruction to add (adapt path to active target):

  • "Before starting tasks, load relevant AEP packs from <agent-dir>/aep/."
  • "Apply task packs first, then project, then user packs."
  • "After successful tasks, save new or updated AEP packs."

Schema Version

All v1.0-exp packs use:

  • "version": "1.0-exp"

See aep-exp/references/schema.v1.md for details.


Additional Concepts

On top of the v0.1 fields, v1.0-exp introduces:

  • applies_to – structured hints for where this pack makes sense:

- languages, frameworks, paths, domains.

  • strength – a single 0–1 score for how strong a match is for typical tasks.
  • metrics – simple counters and timestamps about usage:

- timesapplied, firstusedat, lastusedat, avgturns_saved (optional).

  • history – short records of meaningful changes to the pack.
  • merge_suggestions – optional hints that two packs should be merged or related.

These are experimental and not required for basic interoperability.


Commands (Behavioral Layer)

The four high-level commands stay the same:

  • aep save
  • aep apply
  • aep promote
  • aep inspect

v1.0-exp refines how they populate and use the richer fields.

1. aep save (v1.0-exp)

When the user asks to save the current successful workflow:

  1. Extract signals as in v0.1:

- intent, constraints, preferences, workflow, failuretraps, successchecks.

  1. Infer applies_to from:

- languages and frameworks in use (e.g. "typescript", "nextjs", "python", "django"). - relevant paths (e.g. "app/landing/", "src/api/"). - domain hints (e.g. "frontend", "backend", "infra").

  1. Initialize experimental fields:

- strength: start with a default (e.g. 0.7 for clearly successful tasks). - metrics: - timesapplied: 0 on first creation. - firstusedat: equal to createdat. - lastusedat: equal to createdat. - history: - one entry describing the initial creation (reason, timestamp). - mergesuggestions: leave empty by default.

  1. Resolve install target:

- Detect active agent directory (.claude, .codex, .gemini, .opencode, .cursor). - Set AEP root to <agent-dir>/aep/.

  1. Write pack:

- Save as <agent-dir>/aep/tasks/<id>.aep.json with "version": "1.0-exp". - Update <agent-dir>/aep/index.json: - include version, scope, path, tags, and strength if known.

  1. Update instruction files:

- Update AGENTS.md, CLAUDE.md, and other agent instruction files in this repo to state that AEP should be loaded by default from <agent-dir>/aep/.

  1. Optional evidence:

- Same as v0.1: <agent-dir>/aep/runs/<timestamp-id>/ folder with: - transcript.summary.md, signals.json, outcome.json, generated-pack.json.

2. aep apply (v1.0-exp)

When applying packs before a task:

  1. Resolve install target:

- detect active agent directory and use <agent-dir>/aep/ as source.

  1. Load packs with version "0.1" or "1.0-exp" (backwards compatible).
  2. Compute a match score per pack using:

- keyword/tag overlap (as in v0.1), - applies_to matches: - languages / frameworks, - file paths / domains.

  1. Combine scores:

- final score = f(match_score, pack.strength).

  1. Rank:

- by scope (task > project > user), - then by final score, - then by recency (metrics.lastusedat or index.updated_at).

  1. Update metrics for selected packs:

- increment metrics.timesapplied. - update metrics.lastused_at.

  1. Activate packs and explain:

- merge signals as in v0.1 (task overrides project overrides user). - report: - which packs are active, - their scores and strength, - key constraints and checks.

3. aep promote (v1.0-exp)

Promotion works as in v0.1 but can leverage:

  • metrics and history to identify strong candidates:

- e.g. packs with high times_applied and good user feedback.

  • optional merge_suggestions:

- when two task packs are similar, suggest merging before promotion.

When promoting:

  • add history entries to both source and target packs.
  • optionally record a merge_suggestions note if packs should be merged later.
  • write promoted packs under the active <agent-dir>/aep/ target, not .agent/.

4. aep inspect (v1.0-exp)

In addition to the v0.1 inspection:

  • show:

- applies_to - strength - metrics (how often and how recently a pack was used) - latest history entries

  • highlight:

- if any packs have merge_suggestions involving active packs.


Behavior Rules (v1.0-exp)

  • Maintain backwards compatibility:

- be able to read v0.1 packs and index entries. - when updating, you may choose to migrate a pack to "version": "1.0-exp" (with user approval).

  • Use agent-aware paths:

- prefer .claude/aep, .codex/aep, .gemini/aep, .opencode/aep, .cursor/aep. - do not create .agent/ for new installs.

  • Keep instruction files aligned:

- after creating/updating AEP, ensure AGENTS.md, CLAUDE.md, and other active agent instruction files state that AEP should be loaded first.

  • Keep experimental fields best-effort:

- it is fine if metrics or history are approximate. - do not block core behavior if some fields are missing.

  • Remain transparent and inspectable:

- everything stays JSON/Markdown. - users should be able to edit packs by hand if needed.

For concrete field definitions and templates, see:

  • aep-exp/references/schema.v1.md
  • aep-exp/assets/templates/*.json