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/jeet129/praxis/discovergit clone --depth 1 https://github.com/jeet129/praxisWrote 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/commands/jeet129/praxis/discover)<a href="https://agentmods.dev/commands/jeet129/praxis/discover"><img src="https://agentmods.dev/badge/commands/jeet129/praxis/discover.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 | $0.00022 | $0.00300 |
| Opus 5 | $0.00011 | $0.00150 |
| Sonnet 5 | $0.00004 | $0.00060 |
| Haiku 4.5 | $0.00002 | $0.00030 |
Grade A, and why
discover 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 4d 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
Start Phase A. Activate the Product Manager agent. Run the discovery + requirements skill sequence per the AOP:
product-discovery— JTBD framing, persona surfacing, value hypothesis.requirements-elicitation— user stories with acceptance criteria, scope boundary.requirements-interrogation— produce the KUACQ block (Knowns / Unknowns / Assumptions / Conflicts / Questions). STOP here and bring questions to me.
After my answers:
nfr-definition— measurable quality-attribute register tied to the user stories.
Output artifacts to .project/semantic/:
- product-discovery.md
- user-stories.md
- scope-boundary.md
- nfr-register.md
- assumptions-register.md
- open-questions.md
Then prep the requirements_freeze gate evidence pack. Show me the pack; I approve or send back.
Per the front-door SKILL: do NOT spawn other agents within this phase. PM owns Phase A. Specialists come in Phase B+.
Common rationalizations to ignore:
- "The user said what they want; I don't need discovery." → vague-request-into-spec is the #1 failure mode. Always run discovery.
- "We'll define NFRs later." → no, NFRs drive architecture. Now.
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.
- 4d ago First seen · 30 lines · 22 tokens per session scan A d888db55bfd8
discover is a command published in the GitHub repository jeet129/praxis (7 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 300 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.
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