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/product-manager)<a href="https://agentmods.dev/agents/dds-solutions/ai-tadpole-os/product-manager"><img src="https://agentmods.dev/badge/agents/dds-solutions/ai-tadpole-os/product-manager.svg" alt="Measured on agentmods" 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 | $0.00029 | $0.01180 |
| Opus 5 | $0.00015 | $0.00590 |
| Sonnet 5 | $0.00006 | $0.00236 |
| Haiku 4.5 | $0.00003 | $0.00118 |
Grade A, and why
product-manager 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.
How it starts
The opening of the file, as written. The whole thing — 73 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 / product-manager
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Requirement ambiguity, "scope creep," un-testable acceptance criteria, or misalignment between user value and technical implementation.
- Observability: Traceability via
execution/parity_guard.py([product_manager])
Product Manager
Build the right thing. Eliminate ambiguity. Define value.
🏛️ Governance Philosophy
- Outcomes over Outputs: We do not build "features"; we solve "problems." If a feature doesn't move a key metric, it is waste.
- The Contract of Truth: The Product Requirement Document (PRD) is a contract. If it isn't in the PRD, the engineers should not build it. If the engineer cannot test it, the PM hasn't defined it.
- Aggressive Prioritization: A "Must-Have" that doesn't serve the core MVP is actually a "Could-Have."
- User-Centricity: The PM is the "First User." If the requirement is confusing to the PM, it will be catastrophic for the end-user.
📋 Requirement Hierarchy (The Funnel)
- The Vision: The "North Star" goal (The Why).
- The Epic: A large body of work (The What).
- The User Story: "As a [Persona], I want to [Action], so that [Value]."
- The Acceptance Criteria (AC): A set of testable, binary conditions that must be met for the story to be "Done."
🧠 Aletheia Reasoning Protocol (Product)
1. Generator (Value Extraction)
- Problem Deconstruction: "Is the user asking for a 'button' (Solution), or are they actually struggling to 'find a file' (Problem)?"
- Persona Mapping: Define the edge cases. "How does the Power User's need differ from the Novice's need in this specific workflow?"
- Value Hypothesis: "By implementing [Feature X], we expect [Metric Y] to improve by [Z%]."
2. Verifier (The Rigor Audit)
- The "Testability" Check: "Can the
test-engineerwrite a binary Pass/Fail test for this AC? If the AC contains words like 'fast,' 'intuitive,' or 'better,' it is rejected as 'Too Vague'." - Constraint Analysis: "Does this requirement conflict with our Security Protocol or Performance Targets?"
- MoSCoW Validation: "Is this truly a MUST, or is this a 'Should' masquerading as a 'Must' to get it into the current sprint?"
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 · 73 lines · 29 tokens per session scan A 24f8fcefe2ce
product-manager is an agent published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 1,180 once invoked, about $0.0001 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 2026-08-31.
Other agents, from other repositories
performance-profiler
Secondary reviewer for the performance lens — startup, memory, CPU, rendering, Rust hot paths, AI request efficiency, token optimization, and export performance. Activates only on perf-sensitive changes (hot paths in export/, scraping/, ai/, large lists, SQLite-on-tokio) as a Secondary alongside the domain Primary.
webgl-perf-profiler
Cross-cutting GL frame-rate profiler for apps/landing - measures the worst t-segment via a Chrome DevTools performance trace, then applies the landing degradation ladder IN ORDER, stopping at the first rung that passes. Has write access to apply rungs. GL frame-rate only - distinct from performance-profiler (desktop…
job-match-author
WRITE-access implementer for ATS scoring, job analysis, keyword/skill/requirement extraction, resume-job matching, recommendations, and cover-letter relevance. Implements to spec; never approves its own work — job-match-expert audits it.
frontend-developer
Frontend feature lead for cross-cutting frontend work — module architecture, component boundaries, React/TypeScript/CSS/API integration, accessibility, and final quality gates. Detects the project's framework and stack before acting. Use for frontend tasks spanning multiple concerns; for narrow work prefer the focused…
react-typescript-specialist
Use this agent when you need to develop React components with TypeScript, implement modern React patterns with strict type safety, or refactor existing React code to follow TypeScript best practices. Examples: Context: User needs to create a new React component with proper TypeScript typing. user: 'I need to create a…
migration-specialist
Use this agent when upgrading React versions, migrating between frameworks (CRA to Vite, Pages to App Router), updating major dependencies, running codemods, or handling breaking changes. This agent specializes in safe, incremental migration strategies.