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/asachs01/float-mcp/auto-implement-tasksgit clone --depth 1 https://github.com/asachs01/float-mcpWhat 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 — 11 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 — 108 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 · 108 lines · 0 tokens per session scan A e8c76b6ce8bd
auto-implement-tasks is a command published in the GitHub repository asachs01/float-mcp (2 stars, last pushed 6mo 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 11 lines, and is treated as a copy.
Other commands, from other repositories
pm-done
Close a todo (TODO-xxx), sync completed.md, refresh overview.
pm-status
Show governance health, wizard next step, all open blocking/high todos, and pending review count. Primary daily entry.
pm-charter
Create, import, discover, approve, or skip project charter. No-arg form is an interactive wizard.
pm-check
Diagnose .pm/ health (missing files, broken audit, stale map, unconfirmed PRD) and repair or increment without overwriting confirmed content.
_closing
会改 .pm/ 的 /pm- 回复必须有一句中文摘要。链接只列已经存在的文件，不要指向还没生成的路径。.
context-new
Create a new GitHub repository with AllBeads pre-configured.