implementation-logger
Log implementation decisions — tracks deviations from plan and captures rationale
Skill by jellydn
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/jellydn-implementation-logger
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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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/implementation-logger
What's inside
- Skill name
implementation-logger- Description
- Log implementation decisions — tracks deviations from plan and captures rationale
- License
- MIT
- Compatibility
- cline, claude, opencode, amp, codex, gemini, cursor, pi
- Instructions
- 397 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Implementation Logger ## When to Use Use this skill **during implementation** when: - Working on complex or uncertain changes - The implementation approach isn't fully defined - You want to track decisions for documentation - Building knowledge about unknowns for future work - Need to explain reasoning in PR descriptions ## What It Does Tracks **deviations from the original plan** and **decision rationale** during implementation. Helps identify where your mental model (map) differed from reality (territory). ## How to Execute ### Step 1: Set Up Logging At the start of implementation, create a log file: ```bash # Create implementation log echo "# Implementation Log: [Feature Name]" > .implementation-log.md echo "" >> .implementation-log.md echo "Started: $(date)" >> .implementation-log.md echo "" >> .implementation-log.md echo "## Original Plan" >> .implementation-log.md echo "[Brief summary of approach]" >> .implementation-log.md echo "" >> .implementation-log.md echo "## Deviations & Decisions" >> .implementation-log.md ``` ### Step 2: Log During Implementation Whenever reality differs from plan, log it: ```markdown ### [Timestamp] - [Decision Point Title] **Context**: What I encountered that wasn't in the plan **Original Assumption**: What I thought would work **Reality**: What I actually found **Decision**: What I decided to do instead **Rationale**: Why this approach is better/necessary **Impact**: What else this might affect ``` ### Step 3: Log Categories Track different types of deviations: **Architectural Discoveries**: - Found existing abstraction that changes approach - Realized need for new pattern - Dependency constraints **Unknown Unknowns**: - Edge cases not in spec - Integration points discovered - Performance considerations **Technical Constraints**: - Library limitations - Type system issues - Test infrastructure gaps **Spec Gaps**: - Ambiguous requirements - Missing error handling specs - Unclear business logic ### Step 4: Review & Extract After implementation: 1. Review the log for patterns 2. For each material deviation, compare `expected -> observed -> decision -> verified result` 3. Extract only durable learnings for documentation or skills 4. Identify knowledge to preserve 5. Record "No material deviations" when the plan held; do not invent entries 6. Update relevant docs/ADRs ## Log Template ```markdown # Implementation Log: [Feature Name] **Date**: [Date] **Developer**: [Name or Agent ID] **Original Plan**: [Link to spec/plan] ## Summary [One paragraph: what we built and key decisions] ## Original Approach [What we planned to do] ## Deviations & Decisions ### Decision 1: [Title] **When**: [Timestamp/phase] **Context**: [What prompted this decision] **Original Plan**: [What we thought we'd do] **Reality**: [What we actually found] **Decision**: [What we decided] **Rationale**: [Why this is better] **Impact**: [Side effects or dependencies] **Code**: [Link to relevant commit/files] ### Decision 2: [Title] ... ## Unknowns Discovered
From jellydn/my-ai-tools, MIT.
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Signals
- Stars
- 123
- Forks
- 12
- Open issues
- 3
- Last commit (this folder)
- Oct 7, 2026 (21 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/jellydn/my-ai-tools
- Website
- ai-tools.itman.fyi/
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Posts a concise visual outline as a GitHub pull request comment.
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Build a tight, red-capable feedback loop before diagnosing failures, then minimize, test ranked hypotheses, and lock the fix with a regression test.
SkillAFreshness: A★ 123Claude Code +9 - 0.713score
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Fix PR review comments by implementing requested changes
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Cite this page
implementation-logger skill. Agent Mart. https://agentmart.dev/skills/jellydn-implementation-logger (last updated 2026-10-24)