Use when the user wants to evaluate x-skill alignment and improve a skill based on real session usage — searches Claude Code session history automatically
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Does it follow best practices?
Impact
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No eval scenarios have been run
Advisory
Suggest reviewing before use
Evaluates how well an x-skill was followed during a real session, then improves the skill based on findings.
../x-shared/capability-loading.md. The plugin.omc snapshot token (manifest key plugins.oh_my_claudecode) gates the session_search MCP tool used in step 1; degrade to JSONL-direct fallback if unavailable.For how to invoke skills and agents, see ../x-shared/invocation-guide.md.
Usage:
/x-skill-improve x-do — search recent sessions for x-do usage/x-skill-improve x-research --since 2d — search last 2 days/x-skill-improve x-do /path/to/project abc123 def456 — skill + project dir + multiple sessions/x-skill-improve /path/to/project abc123 def456 — project dir + multiple sessions (auto-detect skill)/x-skill-improve abc123-def456 — single session (auto-detect skill, use current project)/x-skill-improve (no args) — prompt for skill name, then searchTrigger when the user:
Use session_search (MCP tool) to find sessions where the target skill was invoked.
Parse arguments — see references/argument-parsing.md for the full parsing table and resolution rules.
Search and extract — see references/session-discovery.md for discovery queries, fallback ladder, and deep extraction parameters.
mcp.agentmemory pinned in bootstrap-active set): one mcp__plugin_agentmemory_agentmemory__memory_sessions({ limit: 20 }) call plus one mcp__plugin_agentmemory_agentmemory__memory_smart_search({ query: "<skill name + improvement keyword>", limit: 5 }) call. When both succeed, prefer these over the ad-hoc JSONL scan for session discovery. Apply consumer rules from ../x-shared/mcp-toolbox.md § Consumer rules — drop smart-search hits where tags includes auto-import OR confidence < 0.5 before treating them as precedent. When mcp.agentmemory is not pinned, skip silently — Claude's native auto-memory file still applies and the JSONL fallback above remains the path.Read the full skill directory for the identified skill. Resolve location using this precedence:
x- → check plugin source repo first. Resolve dynamically:
${X_SKILLS_PLUGIN_ROOT:-}/skills/<name>/ if env var setgit -C "$dir" config --get remote.origin.url | grep -q x-skills for any candidate from ~/Codes, ~/code, ~/src, $HOME)~/.claude/plugins/cache/x-skills-marketplace/x-skills/*/skills/<name>/ (read-only — never edit here)~/.claude/skills/<name>/<resolved-path>/<skill-name>/
├── SKILL.md # Always read
├── steps/ # Read all if present
├── references/ # Read all if present
├── gotchas.md # Read if present
└── config.json # Read if presentBuild an instruction inventory — a list of every rule, gate, checklist item, and workflow step in the skill.
Walk through the instruction inventory. For each item, classify based on the session:
| Status | Meaning |
|---|---|
| Followed | Execution matched the instruction |
| Deviated | Execution did something different |
| Skipped | Instruction was ignored entirely |
| Worked Around | Execution hit a problem the skill didn't account for |
| N/A | Instruction doesn't apply to this session's mode/type |
Use the analysis rubric in references/analysis-rubric.md for skill-specific checks.
Focus on high-signal misalignments — not every trivial deviation matters. Prioritize:
For each misalignment, present both perspectives:
UPDATE SKILL — The skill is wrong, incomplete, or too rigid. The execution was reasonable.COMPLIANCE GAP — The skill is right. The execution should have followed it.Use the output format below. Then offer to apply fixes.
Use the template in references/output-template.md.
All findings use the shared severity scale:
| Severity | In This Context |
|---|---|
| CRITICAL | Mandatory gate skipped AND skill has no exception for it |
| HIGH | Significant gap — skill missing guidance for a common scenario |
| MEDIUM | Instruction could be clearer or more flexible |
| LOW | Minor wording improvement, edge case documentation |
When the user chooses to apply:
x-* skills, always edit the source repo (resolved per the precedence in step 2: $X_SKILLS_PLUGIN_ROOT, then a local x-skills git checkout). Never edit the plugin cache (~/.claude/plugins/cache/) or installed copy. For standalone skills, edit ~/.claude/skills/<name>/.Edit / Write for all skill edits — surgical partial edits.Updates applied. Validate with
/x-skill-review? [Y] Run review [N] Done
This skill references shared infrastructure in ../x-shared/:
invocation-guide.md — tool invocation patternsseverity-guide.md — finding severity scaleworkflow-chains.md — cross-skill chainingRuntime: Requires session_search MCP tool from the oh-my-claudecode plugin. Falls back to JSONL-direct read of ~/.claude/projects/*/sessions/*.jsonl if unavailable.
After presenting the report, append a summary line to data/alignment-log.jsonl:
{"skill":"x-bugfix","sessionId":"f7035623","date":"2026-04-01","findings":8,"updateSkill":3,"complianceGap":5,"applied":true}This enables cross-session pattern tracking — recurring compliance gaps signal systemic issues.
mcp.agentmemory pinned): one mcp__plugin_agentmemory_agentmemory__memory_save({ content: "<improvement applied to skill X>", type: "lesson", concepts: "<project-slug>:x-skill-improve,<skill-name>,<improvement-class>" }) call (project-slug = basename of cwd — see ../x-shared/mcp-toolbox.md § Consumer rules). Skip silently when not pinned.Updates applied? → Offer /x-skill-review on the modified skill (external user-level skill at ~/.claude/skills/x-skill-review/; if the user has not installed it, surface that fact and stop — do NOT silently no-op the slash command). Primitive: handoff (sync, depends on result). Include a handoff context block: from x-skill-improve, name of the modified skill, list of applied edits with severities, alignment-log entry written. See ../x-shared/workflow-chains.md.
See gotchas.md for known pitfalls — update when you encounter new ones.
Task: {{ARGUMENTS}}
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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.