القائمة
Use when the user wants to review their recent opencode sessions for patterns — analyzes the last N sessions (default 5) in the current project, dispatching parallel reviewers per session, then synthesizing cross-session findings
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Use when analyzing a large corpus of text, code, or data that exceeds a single agent's effective context - orchestrates parallel Worker subagents, Critic review subagents, and a final Summarizer subagent with task tracking and failure recovery
Use to decide what kind of basic agent you should use
Use when creating a new opencode plugin or setting up plugin structure - provides complete file organization, manifest format, and component definitions for commands, agents, skills, hooks, and MCP servers
Use when creating specialized subagents for opencode or the task tool - covers description writing for auto-delegation, tool selection, prompt structure, and testing agents
Use when creating, releasing, or maintaining an opencode Plugin Marketplace - covers marketplace.json schema, version management, release checklists, changelog conventions, and validation to prevent sync drift between plugin.json and marketplace.json
Use when completing development phases or branches to identify and update AGENTS.md files that may have become stale - analyzes what changed, determines affected contracts and documentation, and coordinates updates
| name | review-recent-sessions |
| description | Use when the user wants to review their recent opencode sessions for patterns — analyzes the last N sessions (default 5) in the current project, dispatching parallel reviewers per session, then synthesizing cross-session findings |
Review multiple recent sessions from the current project to identify cross-session patterns.
opencode CLI must be available on PATH (provides opencode session list and opencode export).ed3d-conversation-reviewer agent and the writing-opencode-directives skill must be available (the reviewer loads that skill).scripts/reduce-transcript.py (its absolute path is shown in the file list when this skill loads).The user may ask to:
List the current project's sessions (newest first):
opencode session list
Session IDs match ses_[A-Za-z0-9]+.
Exclude the current session (the user doesn't want to review the review session itself): it is the most recently updated one and its title matches the running conversation — ask the user if it's ambiguous. Never export the active session — a session still being written can truncate mid-write. Take the requested count (default 5) from the remaining sessions.
If fewer than 2 sessions remain, tell the user there aren't enough sessions to do a cross-session review and suggest the review-session skill instead.
Create a working directory, then for each selected session export it and run scripts/reduce-transcript.py (shipped with this skill; its absolute path is shown in the file list when this skill loads):
mkdir -p /tmp/session-review-batch
opencode export <sessionID-N> > /tmp/session-review-batch/session-N.json
python3 scripts/reduce-transcript.py /tmp/session-review-batch/session-N.json /tmp/session-review-batch/reduced-N.txt
This can be done in a single bash command with a loop over the selected session IDs.
For each reduced transcript, dispatch a ed3d-conversation-reviewer agent:
task:
subagent_type: ed3d-conversation-reviewer
description: Review session N of M
prompt: |
Review the reduced opencode session transcript.
Transcript path: /tmp/session-review-batch/reduced-N.txt
Write your findings to: /tmp/session-review-batch/findings-N.md
Read the transcript, analyze it, and write your findings following your output format.
Dispatch ALL reviewers in a single message so they run in parallel; react to completion notifications — do not poll or sleep. Tell the user you've dispatched N reviewers and are waiting for results.
Once all reviewers complete, dispatch a general-purpose Sonnet agent to synthesize:
task:
subagent_type: ed3d-sonnet-general-purpose
description: Synthesize session reviews
prompt: |
You are synthesizing findings from multiple opencode session reviews into a cross-session analysis.
Read all findings files in /tmp/session-review-batch/findings-*.md
Produce a synthesis that identifies:
1. **Recurring patterns** — issues that appear across multiple sessions. These are the highest-value findings because they represent systematic problems.
2. **Progression** — is the user getting better or worse at prompting over time? Is the agent handling certain tasks better or worse?
3. **Highest-impact recommendations** — across all sessions, which recommendations would have the biggest effect? Prioritize:
- AGENTS.md changes (things the user keeps correcting)
- Plugin hooks or permission rules (behaviors that should be enforced automatically)
- Skills/workflows (multi-step processes that keep being done manually)
4. **Session-specific highlights** — any single-session finding that's particularly noteworthy even if it didn't recur.
Write your synthesis to /tmp/session-review-batch/synthesis.md
Format as Markdown. Be specific — reference which sessions showed which patterns. Be concise — this is a summary, not a repetition of individual findings.
Read /tmp/session-review-batch/synthesis.md and present the full synthesis to the user.
If any individual session findings are particularly interesting, mention that the user can find per-session details in /tmp/session-review-batch/findings-N.md.