Skip to main content

ace-analysis

Analyzes sessions using ACE framework to generate prompt improvement suggestions focused on durable patterns.

Informations de source

Dépôt
digi4care/opencode-mastery
Dernière activité de la source
21 février 2026 à 09:55
Langue détectée de SKILL.md
anglais
Étoiles
0
Forks
0

Options d'installation

Le prompt qui vérifie d'abord la source est sélectionné par défaut. Vous pouvez passer à une commande directe ou télécharger une copie locale.

Vérifiez les fichiers source

Lisez SKILL.md et les fichiers associés affichés par SkillsMP avant de décider de l'installer.

Explorateur de fichiers
3 fichiers

Affichage de SKILL.md

SKILL.md
Instructions source · Aperçu en lecture seule
name
ace-analysis
description
Analyzes sessions using ACE framework to generate prompt improvement suggestions focused on durable patterns.
license
MIT
compatibility
opencode
metadata
{"author":"OpenCode Community","version":"1.0.0"}
# ACE Analysis Skill Analyzes AI agent sessions using ACE (Agentic Context Engineering) framework. ## Purpose Evaluate session quality and generate improvement suggestions for prompts, skills, and commands. ## Triggers - `/ace-reflect` command - Session analysis requests - Prompt optimization tasks ## Workflow ### 1. Collect Session Data **Preferred:** `om-session` plugin tools ``` session-list → get recent sessions session-read → get messages from session ``` **Fallback:** OpenCode CLI ```bash opencode session list -n 10 --format json ``` **Last resort:** Direct context analysis (current conversation) ### 2. Determine Analysis Mode | Mode | Flag | Scope | | --------- | ------------- | ----------------------------------- | | Default | (none) | Text analysis, 2-3 findings | | Verbose | `--verbose` | Deeper analysis, more findings | | Technical | `--technical` | Include IDs, timestamps, tool stats | | Full | `--full` | Complete analysis with all metadata | ### 3. Analyze Session Content Focus on **patterns**, not individual mistakes: - Response quality (clarity, accuracy, completeness) - Tool usage efficiency (redundant calls, missing tools) - Context management (pruning, distillation) - Workflow adherence (approval gates, context loading) ### 4. Score Session Use scoring rubric from `references/scoring-rubric.md`: | Criterium | Weight | Focus | | ------------ | ------ | ------------------------------------ | | Completeness | 5 | All requested tasks completed | | Accuracy | 5 | Correct solutions, no hallucinations | | Efficiency | 5 | Minimal iterations, good tool usage | | Clarity | 5 | Clear communication, good structure | | Relevance | 5 | On-topic, no unnecessary tangents | **Max Score:** 25 ### 5. Generate Report Use template from `references/report-template.md`: - Summary (1-2 sentences) - Scores table - Findings (patterns, not individual mistakes) - Suggestions (specific, actionable) - Decision (no changes / review / changes recommended) ### 6. Return to Orchestrator Return formal report for presentation to user. ## References - `references/report-template.md` - Report structure - `references/scoring-rubric.md` - Detailed scoring criteria ## Error Handling | Situation | Action | | -------------------- | -------------------------------- | | No session data | Analyze current context directly | | Plugin unavailable | Use CLI fallback | | Subagent spawn fails | Analyze in current context | ## Configuration ```yaml features: ace: enabled: true max_subagent_depth: 2 auto_apply_suggestions: false ```
Voir sur GitHub