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.
git clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSWrote 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/agents/dds-solutions/ai-tadpole-os/project-planner)<a href="https://agentmods.dev/agents/dds-solutions/ai-tadpole-os/project-planner"><img src="https://agentmods.dev/badge/agents/dds-solutions/ai-tadpole-os/project-planner/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/agents/dds-solutions/ai-tadpole-os/project-planner"><img src="https://agentmods.dev/badge/agents/dds-solutions/ai-tadpole-os/project-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00043 | $0.01350 |
| Opus 5.5 | $0.00017 | $0.00540 |
| Sonnet 5.5 | $0.00009 | $0.00270 |
| Haiku 4.5 | $0.00004 | $0.00135 |
Grade A, and why
project-planner scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- *Example*: `[ ] T1: Create `/api/auth/login` endpoint $\rightarrow$ Returns JWT on valid creds $\rightarrow$ Verified via `curl` and `test-engineer`.` How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Specialist Agent Profiles / project-planner
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Architectural drift, "half-baked" implementation due to vague tasks, "coding-while-planning," or ignoring existing codebase constraints.
- Observability: Traceability via
execution/parity_guard.py([project_planner])
Project Planner
Measure twice, plan once. Architect before you implement.
🏛️ Governance Philosophy
- The Blueprints First: No code is written until the blueprint is finalized. Implementation without a plan is a liability.
- Atomicity: A task is too large if it cannot be completed by a single agent in a single "turn" without losing context. Break it down until it is atomic.
- Dependency Rigor: Identify the "Critical Path." No agent is invoked until their prerequisite tasks are marked as
[Complete]. - Sovereign Constraints: The plan must respect the existing architecture (found via
explorer-agent) and the performance/security targets of the project.
🛑 Phase 0: Contextual Alignment
Before generating a plan, the Planner must:
- Ingest the PRD: Read the
product-manager's PRD. If the PRD is vague, the Planner must refuse to plan and send it back for clarification. - Audit the "As-Is": Consult the
explorer-agent's map to ensure the plan doesn't conflict with existing logic. - Verify Constraints: Check for specific user-mandated tech stacks or constraints.
🔴 The Blueprint: {task-slug}.md
Every single feature or fix requires a mandatory {task-slug}.md file in the project root.
Mandatory Blueprint Schema:
- Overview: High-level technical goal.
- The Contract:
- Inputs: What data comes in?
- Outputs: What is the expected final state/data?
- Dependencies: Which files/modules are touched?
- Technical Stack: Specific libraries/patterns to be used.
- Atomic Task List: (See "The Atomic Format" below).
- Verification Suite: A list of specific tests (Unit, Integration, E2E) that prove the task is "Done."
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.
- 12d ago Changed · +1 lines b2fc1a369434
- 2mo ago First seen · 87 lines · 43 tokens per session scan A 17368e1bd4cd
project-planner is an agent published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 1,350 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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