execution-report
Use when generating an implementation report after feature completion documenting what was done, divergences from plan, and test results
Skill by giladresisi
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/giladresisi-execution-report
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: documents, testing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/execution-report
What's inside
- Skill name
execution-report- Description
- Use when generating an implementation report after feature completion documenting what was done, divergences from plan, and test results
- License
- MIT
- Instructions
- 191 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Execution Report
Review and deeply analyze the implementation you just completed.
## Context
You have just finished implementing a feature. Before moving on, reflect on:
- What you implemented
- How it aligns with the plan
- What challenges you encountered
- What diverged and why
## Step 1: Read PROGRESS.md
**MANDATORY FIRST STEP:**
1. Read `PROGRESS.md` to find the execution phase notes for this feature
2. Review what was accomplished and what's left to do
3. Use this context to inform your execution report
## Generate Report
**CRITICAL: Create report in `.agents/execution-reports/` folder**
### Step 1: Determine Feature Name
Extract the feature/module name from PROGRESS.md or the plan file path.
Example: "module-5-multi-format-enhancement" from plan path `.agents/plans/module-5-multi-format-enhancement.md`
### Step 2: Summarize Test Coverage
Before writing the report, inspect the test files that were added or modified during this implementation:
1. Use `git diff --name-only HEAD` (or diff against the base branch) to identify changed files
2. Filter for test files (files under `tests/`, named `test_*.py`, `*.test.ts`, `*.spec.*`, etc.)
3. For each changed test file, read it and identify:
- What functions/endpoints/behaviors are tested
- What scenarios are covered (happy path, error cases, edge cases)
4. Produce a concise bulleted list — one sentence per item — capturing what each test validates
You will include this list in the report under `## What was tested`.
### Step 3: Create Detailed Execution Report
**Create file:** `.agents/execution-reports/{feature-name}.md`
**Use Write tool to create this file with the following structure:**
```markdown
# Execution Report: [Feature Name]
**Date:** [Current date]
**Plan:** [path to plan file]
**Executor:** [team-based/sequential/etc]
**Outcome:** ✅ Success / ⚠️ Partial / ❌ Failed
---
## Executive Summary
[2-3 sentence summary of what was implemented and outcome]
**Key Metrics:**
- **Tasks Completed:** X/Y (Z%)
- **Tests Added:** X
- **Test Pass Rate:** X/Y (Z%)
- **Files Modified:** X
- **Lines Changed:** +X/-Y
- **Execution Time:** ~X minutes
- **Alignment Score:** X/10
---
## Implementation Summary
[Detailed breakdown of what was implemented, organized by phase/wave/category]
---
## Divergences from Plan
### Divergence #1: [Title]
**Classification:** ✅ GOOD / ❌ BAD / ⚠️ ENVIRONMENTAL
**Planned:** [what plan specified]
**Actual:** [what was implemented]
**Reason:** [why divergence occurred]
**Root Cause:** [plan gap, environmental, framework behavior, etc]
**Impact:** [positive/negative/neutral - describe]
**Justified:** Yes/No
[Repeat for each divergence]
---
## Test Results
**Tests Added:** [list with descriptions]
**Test Execution:** [show test output summary]
**Pass Rate:** X/Y (Z%)
---
## What was tested
[Bulleted list — one sentence each — describing what each test validates. Derived from inspecting changed test files (Step 2 above). Focus on the scenario/behavior, not the file name.]
- [e.g., `POST /ingest` returns 422 when the payload is missing required fields]
- [e.g., Semantic search returns ranked results ordered by cosine similarity]
- [e.g., KB entry creation is atomic — partial writes are rolled back on failure]
---
## Validation Results
| Level | Command | Status | Notes |
|-------|---------|--------|-------|From giladresisi/ai-dev-env, MIT.
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Use when an agent executing an implementation plan claims to have finished, to validate that all acceptance criteria were actually met.
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Use when a feature is complete and PROGRESS.md needs cleaning up by replacing verbose execution notes with a concise completion summary
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Use when performing a technical pre-commit code review on recently changed files for bugs, security issues, and standards compliance
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Use when loading project context and architecture overview before starting implementation work, with optional focus on a specific area
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Use when performing a meta-level analysis of plan adherence after implementation to identify process improvements and suggest CLAUDE.md updates
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Signals
- Stars
- 2
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Mar 6, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/giladresisi/ai-dev-env
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Use when creating a git worktree for feature isolation with automatic environment setup including .env files and dependency installation
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plan-feature
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Use when creating a comprehensive implementation plan for a new feature including codebase analysis, API research, and parallel execution strategy
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Use when an agent is asked to define, review, or write acceptance criteria for a request or plan.
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Creates a new git worktree in the auto-co-trader project for any purpose — optimization, regression, backtesting, brainstorming, etc.
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execute
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Use when implementing a feature plan file, choosing between sequential and team-based parallel execution with mandatory validation gates
SkillCFreshness: C★ 2Claude Code +9 - 0.443score
cleanup-progress
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Use when a feature is complete and PROGRESS.md needs cleaning up by replacing verbose execution notes with a concise completion summary
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Cite this page
execution-report skill. Agent Mart. https://agentmart.dev/skills/giladresisi-execution-report (last updated 2026-10-24)