Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSnpx agentmods add skills/dds-solutions/ai-tadpole-os/plan-writingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/plan-writing)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/plan-writing"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/plan-writing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/plan-writing"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/plan-writing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00031 | $0.00558 |
| Opus 5 | $0.00015 | $0.00279 |
| Sonnet 5 | $0.00006 | $0.00112 |
| Haiku 4.5 | $0.00003 | $0.00056 |
Grade A, and why
plan-writing 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 8d 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.
What it actually says
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / plan-writing
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Information drift, legacy terminology, or documentation mismatch.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
Structured Plan Writing Protocol
Purpose: Convert complex requirements into actionable, atomic tasks with concrete verification gates. Workflow Binding: Used directly during the
/planworkflow.
🎯 Progressive Disclosure & L3 Reference Index
Read REQUIRED planning rules below; consult deep L3 Reference Guides on demand:
| L3 Reference Guide | Purpose | Trigger / When to Load |
|---|---|---|
references/implementation_plan_templates.md |
Feature blueprints, expand-contract slicing guides, verification checklists | Drafting architectural implementation plans |
📐 1. Task Breakdown Principles
- Keep It Short: Aim for 5–10 clear, focused tasks maximum.
- Be Specific: Specify exact file paths, line ranges, and function names (e.g.
src/services/agent_service.ts). - Atomic Verification: Every single task must include an explicit verification step (
Verify: npm test). - Slicing Strategy:
- Feature Work: Vertical tracer bullets (schema ➔ backend route ➔ frontend state ➔ UI).
- Wide Refactors: Expand-Contract slicing (Expand new ➔ Migrate callers ➔ Contract old).
🧭 2. Plan Structure Format
# [Task Title]
## 1. Goal
One-sentence statement of what we are building or fixing.
## 2. Tasks
- [ ] Task 1: [Specific modification] ➔ Verify: [Test command / check]
- [ ] Task 2: [Specific modification] ➔ Verify: [Test command / check]
## 3. Final Verification Gate
- Automated tests: `npm run test && cargo test`
- Parity check: `python execution/parity_guard.py .`
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 58 lines · 31 tokens per session scan A f42757261c86
plan-writing is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 558 once invoked, about $0.0002 per session on Opus 5. 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 2026-09-03.
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