Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
日本語の概要は準備中です。原文の説明を表示しています。
Turn vague "what did I do?" into evidence-backed impact statements for performance reviews, self-reviews, promotion packets, and weekly updates. Uniquely mines Copilot CLI session logs to reconstruct forgotten work, plus git commits and GitHub PRs. Enforces a 3-part impact contract (action → result → evidence). Works standalone with zero dependencies. Trigger for: "brag", "log work", "what did I do", "backfill my work history", "performance review", "self-review", "self assessment", "write impact statement", "review prep", "promo packet", "promotion case", "weekly update", "status report", "accomplishments", "what did I ship", "I forgot to log my work", "summarize my work", "track my wins", "what should I highlight", "end of half", "career growth", "work journal", or any request to document, summarize, or organize work accomplishments.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Attribution: Sourced from github/awesome-copilot by GitHub Community, licensed MIT. Modified for this collection.
Turn engineering work into evidence-backed impact statements for performance reviews, self-reviews, promotion packets, and weekly updates. Uniquely mines Copilot CLI session logs, git history, and PRs to reconstruct forgotten work.
USE FOR: "brag", "log work", "what did I do", "backfill", "performance review", "self-review", "promo packet", "weekly update", "status report", "write impact statement", "what did I ship", "I forgot to log my work", "review prep", "accomplishments" DO NOT USE FOR: project management, sprint planning, time tracking, ticket creation
| User wants... | Mode | Output |
|---|---|---|
| Log one accomplishment | Capture | 1 impact-first entry |
| "What did I do last week?" | Backfill | Entries grouped by week, mined from git/PRs/sessions |
| Prep for review or promo | Review Pack | Entries grouped by impact theme + STAR narratives |
save_to_brag_sheet, git, gh) before choosing a workflow.(evidence needed) — never silently omit.Every entry uses impact-first framing with three required parts:
Did [action] → [result/impact] → [evidence]
Do not output an entry unless it includes all three parts. If evidence is missing, ask for it or mark as "(evidence needed)".
| ❌ Don't | ✅ Do instead |
|---|---|
| "Fixed a bug in auth" | "Fixed token refresh race condition → eliminated 401s affecting 12% of API calls → PR #247" |
| "Worked on dashboards" | "Built latency dashboard in Grafana → on-call detects P95 spikes in <2min → deployed to prod" |
| Invent a metric: "saved 40% of eng time" | Ask: "Do you have a rough estimate, or should I keep this qualitative?" |
| One entry per commit | Group related commits into one entry with highest-impact framing |
| Passive voice: "The pipeline was improved" | Active voice: "Built CI matrix → caught Windows-only bug before release" |
| List technologies used | State the outcome: "Migrated 4 services to IaC → deploy time 45min → 8min" |
| Silently drop weak entries | Mark (evidence needed) and present for user to fill in |
Not every entry needs a metric. Use the strongest evidence available:
| Strength | Evidence type | Example |
|---|---|---|
| 🥇 Best | Quantified metric | "Reduced P95 latency from 800ms to 120ms" |
| 🥈 Strong | PR, commit, or doc link | "PR #312, design doc in wiki" |
| 🥉 Good | Observable outcome | "Unblocked Team X", "Resolved Sev2 incident Y" |
| ✅ Acceptable | Qualitative + context | "Reduced toil for on-call rotation — see updated runbook" |
| ⚠️ Weak | Activity only | "Worked on auth" — reframe or mark (evidence needed) |
Never invent a metric to fill the gap. Qualitative evidence with context beats fabricated numbers.
| ID | Emoji | Use for |
|---|---|---|
pr | 🚀 | Merged PRs, shipped features |
bugfix | 🐛 | Bug fixes, incident patches |
infrastructure | 🏗️ | Infra, deployments, migrations |
investigation | 🔍 | Root cause analysis, debugging |
collaboration | 🤝 | Reviews, mentoring, design discussions |
tooling | 🔧 | Dev tools, scripts, automation |
oncall | 🚨 | Incident response, on-call wins |
design | 📐 | Design docs, architecture decisions |
documentation | 📝 | Docs, runbooks, guides |
Follow this decision tree:
If save_to_brag_sheet tool is available → use extension tools directly (save_to_brag_sheet, review_brag_sheet, generate_work_log). Do not reference or attempt to call these tools unless they are confirmed available.
If git or gh CLI is available → backfill from commits and PRs (see Backfill section below)
Otherwise → guided interview: "What did you work on?", "Who benefited?", "What's the evidence?"
For each entry, walk through: What (the deliverable) → Why (who benefits) → Evidence (PR, metric, link). Output formatted markdown the user can paste into a review doc.
When the user asks "what did I do last week" or "backfill my history":
Follow these steps in order. Do not draft entries until scanning is complete.
Check what's available, then mine each source:
git --version 2>/dev/null # for commit mining
gh --version 2>/dev/null # for PR mining
ls ~/.copilot/session-state/ 2>/dev/null # Copilot session logs
Git commits — recent commits by the user in the current repo:
git log --author="$(git config user.email)" --since="2 weeks ago" \
--pretty=format:'%h|%ad|%s' --date=short --no-merges
PR history — merged PRs across repos:
gh pr list --author @me --state merged --limit 20 \
--json number,title,repository,mergedAt
Copilot session history (unique to this skill):
~/.copilot/session-state/<session-id>/workspace.yamlsummary, cwd, repository, branchsummary fieldIf none of these sources are available, fall back to the guided interview.
Cluster related signals into one entry:
Write impact-first entries for each group. Assign categories.
Show all drafted entries to the user. Adjust based on feedback.
Format as markdown grouped by week:
## Week of 2025-04-14
### 🚀 PRs & Features
- **Migrated auth service to managed identity** → eliminated 3 secret rotation incidents/quarter → PR #312
### 🏗️ Infrastructure
- **Built CI pipeline for copilot-brag-sheet** → 107 tests across 3 OSes × 3 Node versions → shipped v1.0.0
When the user is preparing for a performance review (Connect, annual review, etc.):
| ✅ Strong | ❌ Weak |
|---|---|
| Outcome-first, quantified | Activity list ("worked on X") |
| Tied to customer/team impact | No beneficiary mentioned |
| Includes evidence (PR, metric) | No measurable result |
| Shows ownership or leadership | Pure task completion |
For longer narrative sections, use STAR: Situation → Task → Action → Result.
For Microsoft employees using the Connect preset, frame entries around Core Priorities: delivering results, customer obsession, teamwork, and growth mindset.
Before finishing, ensure:
(evidence needed) if missing)The user may work across multiple repos. Before concluding there's nothing to backfill:
gh pr list --author @me --state merged for cross-repo PRsPerformance reviews often cover 6–12 months. Explicitly set the date range:
git log --author="$(git config user.name)" --since="2024-07-01" --until="2025-01-01" --oneline
PR history (gh pr list --state merged) is more reliable for long time ranges than commit logs.
Not every entry needs a number. See the Evidence Ladder above. Acceptable evidence includes PR links, "unblocked Team X", or qualitative outcomes with context. Never invent a metric to fill the gap.
~/.copilot/session-state/ only exists if the user has run Copilot CLI sessions. Don't error — silently skip and note: "No Copilot session history found; scanning git and PRs only."
The user might say "brag about this feature to my team" (a launch announcement, not a work entry). Confirm intent if ambiguous.
If multiple authors appear on the same commits, ask: "Should I credit this as your work, shared work, or skip it?"
For automatic background tracking of every Copilot CLI session (files edited, PRs created, git actions), install the copilot-brag-sheet extension. It adds save_to_brag_sheet, review_brag_sheet, and generate_work_log tools to every session.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
日本語の概要は準備中です。原文の説明を表示しています。
Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.
日本語の概要は準備中です。原文の説明を表示しています。
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
日本語の概要は準備中です。原文の説明を表示しています。
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
日本語の概要は準備中です。原文の説明を表示しています。
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
日本語の概要は準備中です。原文の説明を表示しています。