From pensyve
Pre-refactor context loading -- queries Pensyve memory for past decisions, failures, and patterns related to a refactoring target, then compiles a briefing. Use when starting a refactor to avoid repeating past mistakes.
npx claudepluginhub sumeet138/qwen-code-agents --plugin pensyveThis skill uses the workspace's default tool permissions.
Load historical context from Pensyve memory before starting a refactor. Surfaces past decisions, failed approaches, known pitfalls, and relevant patterns to avoid repeating mistakes.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Searches prompts.chat for AI prompt templates by keyword or category, retrieves by ID with variable handling, and improves prompts via AI. Use for discovering or enhancing prompts.
Guides implementation of event-driven hooks in Claude Code plugins using prompt-based validation and bash commands for PreToolUse, Stop, and session events.
Load historical context from Pensyve memory before starting a refactor. Surfaces past decisions, failed approaches, known pitfalls, and relevant patterns to avoid repeating mistakes.
When this skill is invoked with a refactoring target, follow these steps:
Run multiple pensyve_recall queries to gather comprehensive context about the target:
pensyve_recall with query "<target>" (limit: 10)pensyve_recall with query "<target> refactor" (limit: 5)pensyve_recall with query "<target> failed" (limit: 5)pensyve_recall with query "<target> error" (limit: 5)pensyve_recall with query "<target> decided" (limit: 5)pensyve_recall with query "<target> depends" (limit: 5)If the target matches an entity name, also call pensyve_inspect with entity: "<target>" to get the full memory inventory for that entity.
Organize the findings into a structured briefing. Deduplicate results that appear across multiple queries.
Refactor Briefing:
<target>Known Facts
- List of semantic memories about the target, ordered by confidence
- Include confidence scores
Past Decisions
- Architecture or design decisions related to this target
- Include the reasoning if available ("chose X because Y")
Past Outcomes
- Previous refactoring attempts and their results
- Bug fixes and their root causes
- What worked and what did not
Known Pitfalls
- Failed approaches (flagged clearly so they are not repeated)
- Edge cases or gotchas discovered in past sessions
- Dependencies that may be affected
Procedural Knowledge
- Action-outcome patterns with reliability scores
- Proven workflows related to this target
Recommendations
- Synthesize the above into 2-5 actionable recommendations
- Flag any conflicts or contradictions in the memory
Memory Gaps
- Areas where no relevant memories exist
- Suggest what to watch for during the refactor
If no relevant memories are found for a section, omit that section entirely rather than showing an empty one. If no memories are found at all, say so clearly and proceed without historical context.
After presenting the briefing, offer to track the refactor as an episode:
Would you like me to track this refactor as an episode? This will let Pensyve capture the decisions and outcomes from this session for future reference.
If yes, I will call
pensyve_episode_startwith participants["claude-code", "<target>"].
If the user accepts, call pensyve_episode_start. Remind the user to close the episode at the end of the refactor (or suggest using /consolidate or the session-memory skill).
.claude/ memory files. All memory operations go through the Pensyve MCP tools exclusively.pensyve_recall returns errors on some queries, present results from the successful queries and note the failures.pensyve_inspect fails, skip the entity inspection and rely on recall results.pensyve_episode_start fails when the user accepts tracking, report the error but do not block the refactor.