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/dgunning/edgartools/plangit clone --depth 1 https://github.com/dgunning/edgartoolsWhat 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 | $0.01729 |
| Opus 5 | $0.00000 | $0.00864 |
| Sonnet 5 | $0.00000 | $0.00346 |
| Haiku 4.5 | $0.00000 | $0.00173 |
Grade A, and why
plan 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- plan — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Plan
You are tasked with creating a detailed implementation plan based on research findings. This is Phase 2 of the Frequent Intentional Compaction (FIC) workflow.
Initial Setup:
When this command is invoked, respond with:
📋 Starting implementation planning (Phase 2 of FIC workflow)
I'll create a detailed implementation plan based on the research findings.
Please provide either:
1. The path to your research document from Phase 1, or
2. A summary of what needs to be implemented
Planning Process:
1. Context Gathering
If research document exists:
- Read the research document from Phase 1
- Extract key findings and open questions
- Identify components that need modification
- For GitHub issues: Extract reproduction steps and root cause
If starting fresh:
- Detect if input is a GitHub issue (#NNN)
- If issue: Read the issue research or fetch with
gh issue view - Otherwise: Conduct quick research using the codebase-locator agent
- Identify key files and patterns
- Understand current implementation
2. Analyze Requirements
- Clarify the desired outcome
- Identify constraints and dependencies
- Consider EdgarTools principles:
- Simple yet powerful
- Beginner-friendly
- Accurate financials
- Joyful UX with rich output
3. Design Solution
Break down the implementation into logical phases:
- Each phase should be independently testable
- Phases should build on each other
- Include verification steps for each phase
- Consider rollback strategies if needed
4. Create Detailed Plan Document
Save to: docs-internal/planning/active-tasks/YYYY-MM-DD-{topic}-plan.md
Structure:
# Implementation Plan: [Feature/Fix Name]
**Date Created**: [Current date]
**Planning Phase**: 2 of 3 (FIC Workflow)
**Based on Research**: [Link to research document if exists]
**Next Phase**: Implementation (`/implement`)
## Overview
[Brief description of what will be implemented and why]
## Current State Analysis
[Summary from research phase]
- What exists today
- Key files involved
- Current limitations
## Desired End State
[Clear description of success]
- Functional requirements
- Performance requirements
- User experience goals
## Out of Scope
[What will NOT be addressed]
- Future enhancements
- Unrelated improvements
- Items for separate tasks
## Implementation Approach
### Phase 1: [Descriptive Name] ⬜
**Goal**: [What this phase accomplishes]
**Changes**:
1. `edgar/module.py`:
- [ ] Add method `new_functionality()`
- [ ] Update class initialization
```python
# Example of key change
def new_functionality(self):
# Implementation approach
pass
tests/test_module.py:- Add test for new functionality
- Update existing tests
Verification:
- Run:
python -m pytest tests/test_module.py - Check: New functionality works with sample data
- Verify: No regression in existing features
Phase 2: [Descriptive Name] ⬜
Goal: [What this phase accomplishes]
Changes: [Similar structure to Phase 1]
Verification: [Specific tests and checks]
Phase 3: [Integration and Polish] ⬜
Goal: Complete integration and user experience
Changes:
- Documentation updates
- Example scripts
- Performance optimization
- Rich output formatting
Verification:
- All tests pass:
python -m pytest - Documentation builds:
mkdocs build - Examples run successfully
- Performance meets requirements
Testing Strategy
Unit Tests
- New test files needed
- Existing tests to update
- Coverage requirements
Integration Tests
- End-to-end scenarios
- Edge cases to handle
- Performance benchmarks
Manual Verification
- User workflows to test
- Visual output checks (rich formatting)
- Error handling scenarios
Risk Mitigation
Potential Issues
-
Issue: [Potential problem] Mitigation: [How to handle]
-
Issue: [Another potential problem] Mitigation: [How to handle]
Rollback Plan
- How to revert changes if needed
- Backup strategies for critical data
Dependencies
- External libraries required
- Internal modules affected
- Documentation updates needed
Success Criteria
- All functional requirements met
- Tests pass with >90% coverage for new code
- Documentation complete
- No performance regression
- Clean code following EdgarTools patterns
Estimated Effort
- Phase 1: [Time estimate]
- Phase 2: [Time estimate]
- Phase 3: [Time estimate]
- Total: [Total estimate]
Notes for Implementation
- Key EdgarTools patterns to follow
- Specific gotchas to watch for
- Performance considerations
- Security considerations (API keys, rate limits)
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 · 272 lines · 0 tokens per session scan A 273e60f12975
plan is a command published in the GitHub repository dgunning/edgartools (2,635 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,729 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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.