القائمة
Search erinra for stored memories
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
Run parallel code review agents and consolidate findings into a unified report
Capture a follow-up idea or task as a work-item draft without interrupting current work. Use to quickly jot down something you think of mid-task so it gets tracked. Works with nibs, GitHub, Azure DevOps, or a Markdown fallback.
Take an under-specified work item and make it actionable — resolve its open questions through a short interview grounded in the code, and give it acceptance criteria. Use on a captured draft, or any item too vague to start on.
Reconcile what was built against what was planned, record decisions and deviations, close the item (a single phase or a whole plan), and file follow-ups for deferred work. Use after finishing a phase or plan to keep planned and actual from drifting apart.
Orchestrate execution of MULTIPLE nibs in one run. Selects a queue, understands the nibs collectively (including how they fit together), then chooses the best execution mechanism per cluster — single series agent, parallel fan-out, scripted workflow, or agent team — and dispatches with ONE approval gate. Use when the user wants to work several nibs together (in parallel or series) rather than one at a time. Complements /decaf-build:auto-dev and /decaf-build:auto-tdd (which handle a single nib).
Direct development with automated review. Plans implementation, executes via subagent, then auto-reviews. Use for work that isn't test-driven (UI, config, styling, infrastructure, scaffolding).
| name | recall |
| description | Search erinra for stored memories |
| argument-hint | [search query] |
Search erinra for previously stored memories.
Check that mcp__erinra__search is available in your tools. If not, tell the user:
Erinra MCP server is not connected. Run
claude mcp add erinra -- erinra serve -s userand restart Claude Code.
/decaf-memory:recall [search query]
Examples:
/recall HttpClient timeout — Find memories about HttpClient timeouts/recall user preferences — Retrieve stored user preferences/recall polly retry — Find patterns about Polly retry policiesSearch using mcp__erinra__search with the user's query:
mcp__erinra__search({
query: "[user's search terms]",
limit: 10
})
Display results showing:
If no results, suggest:
/decaf-memory:remember to store something newUse filters to narrow results:
mcp__erinra__search({
query: "[search terms]",
projects: ["project-name"], // Filter by project (OR across projects)
type: "pattern", // Filter by exact type
tags: ["dotnet", "async"], // Filter by tags (AND — must have all)
include_archived: false, // Default: false
limit: 10
})
Narrow by when memories were created or last updated:
mcp__erinra__search({
query: "[search terms]",
created_max_age_days: 30, // Created within the last 30 days
updated_after: "2025-01-01T00:00:00Z" // Updated after a specific date
})
Available time filters: created_after, created_before, updated_after, updated_before, created_max_age_days, created_min_age_days, updated_max_age_days, updated_min_age_days.
To browse memories without a search query, use mcp__erinra__list instead:
mcp__erinra__list({
projects: ["project-name"],
type: "decision",
limit: 20
})
This supports the same filters as search but returns paginated results with a total count.
Search results may truncate long content. To get the full text of a memory:
mcp__erinra__get({ ids: ["[memory-id]"] })
Search results include outgoing and incoming links. To follow a link and see the related memory:
mcp__erinra__get({ ids: ["[linked-memory-id]"] })