Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/snarktank/code-editing-agent/auto-implement-tasksgit clone --depth 1 https://github.com/snarktank/code-editing-agentWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00469 |
| Opus 5 | $0.00000 | $0.00234 |
| Sonnet 5 | $0.00000 | $0.00094 |
| Haiku 4.5 | $0.00000 | $0.00047 |
Grade A, and why
auto-implement-tasks scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to auto-implement-tasks — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Enhanced auto-implementation with intelligent code generation and testing.
Arguments: $ARGUMENTS
Intelligent Auto-Implementation
Advanced implementation with context awareness and quality checks.
1. Pre-Implementation Analysis
Before starting:
- Analyze task complexity and requirements
- Check codebase patterns and conventions
- Identify similar completed tasks
- Assess test coverage needs
- Detect potential risks
2. Smart Implementation Strategy
Based on task type and context:
Feature Tasks
- Research existing patterns
- Design component architecture
- Implement with tests
- Integrate with system
- Update documentation
Bug Fix Tasks
- Reproduce issue
- Identify root cause
- Implement minimal fix
- Add regression tests
- Verify side effects
Refactoring Tasks
- Analyze current structure
- Plan incremental changes
- Maintain test coverage
- Refactor step-by-step
- Verify behavior unchanged
3. Code Intelligence
Pattern Recognition
- Learn from existing code
- Follow team conventions
- Use preferred libraries
- Match style guidelines
Test-Driven Approach
- Write tests first when possible
- Ensure comprehensive coverage
- Include edge cases
- Performance considerations
4. Progressive Implementation
Step-by-step with validation:
Step 1/5: Setting up component structure ✓
Step 2/5: Implementing core logic ✓
Step 3/5: Adding error handling ⚡ (in progress)
Step 4/5: Writing tests ⏳
Step 5/5: Integration testing ⏳
Current: Adding try-catch blocks and validation...
5. Quality Assurance
Automated checks:
- Linting and formatting
- Test execution
- Type checking
- Dependency validation
- Performance analysis
6. Smart Recovery
If issues arise:
- Diagnostic analysis
- Suggestion generation
- Fallback strategies
- Manual intervention points
- Learning from failures
7. Post-Implementation
After completion:
- Generate PR description
- Update documentation
- Log lessons learned
- Suggest follow-up tasks
- Update task relationships
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 97 lines · 0 tokens per session scan A e03f4552cc01
auto-implement-tasks is a command published in the GitHub repository snarktank/code-editing-agent (24 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 469 tokens. A static security scan graded it A with 0 findings. It is 100% identical to auto-implement-tasks, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.