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 skills/boshu2/agentops/productnpx skills add boshu2/agentops --skill productgit clone --depth 1 https://github.com/boshu2/agentopsWrote 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/boshu2/agentops/product)<a href="https://agentmods.dev/skills/boshu2/agentops/product"><img src="https://agentmods.dev/badge/skills/boshu2/agentops/product.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 | $0.00037 | $0.00581 |
| Opus 5 | $0.00018 | $0.00291 |
| Sonnet 5 | $0.00007 | $0.00116 |
| Haiku 4.5 | $0.00004 | $0.00058 |
Grade A, and why
product 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 3d 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
Product
Create or refine a product contract with the user's authority.
The contract works because it forces every claim into evidence or labeled aspiration; if a reader cannot tell which is which, the document has failed.
- Inspect existing product, README, goals, release, and evidence sources.
- Ask only for decisions that cannot be grounded safely from those sources.
- State mission, users, pains, value, differentiation, and non-goals. For
this repository's own product surfaces, start from the canonical category
in
docs/contracts/ubiquitous-language.md(AgentOps is the operations layer for agentic engineering) and preserve the small ownership boundary — never re-frame AgentOps as an execution orchestrator, factory, or loop. - Separate evidence from hope under two required headings. Put every grounded
claim under
## Proven, each carrying a resolvable citation (a README, release, test, or evidence source). Put unproven hopes, evidence gaps, and not-yet-measured success signals under## Assumptions. A claim that cannot cite a source belongs under## Assumptions, never## Proven. - Preserve an existing PRODUCT.md unless the user authorizes replacement.
- Return the document to the caller; Plan may use it as intent context.
Named failure mode — aspiration laundering: an unproven hope written in the
## Proven section; once laundered, every downstream plan inherits a false
premise. Detector: any ## Proven claim without a resolvable citation is a
laundered aspiration — move it to ## Assumptions or cite it.
Anti-pattern: rewriting a healthy PRODUCT.md wholesale because the session has fresh opinions. Corrective: refine only the sections the user asked to change and preserve the rest byte-for-byte.
Product does not select work, invoke a loop, repair itself, validate itself, or choose delivery.
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.
- 3d ago First seen · 60 lines · 37 tokens per session scan A 6c4b1508889b
product is a skill published in the GitHub repository boshu2/agentops (431 stars, last pushed 5d ago), licensed Apache-2.0. It adds 37 tokens to every session and 581 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 2026-08-30.
Other skills, from other repositories
brainstorm
Explore vague or ambitious ideas into a right-sized requirements-only plan. Use when the user wants to brainstorm, think through scope, decide what to build, or needs collaborative product framing before planning, not for a decisive verdict on whether to adopt or switch to a specific external technology, library, or…
doc-review
Use when the user asks to review or critique a prose planning document — a plan, spec, PRD, requirements doc, or design doc.
audit-project
Run an iterative multi-agent code audit until critical and high findings are resolved. Use when the user says "audit my code", "find all the bugs", "deep code audit", "iterative review", or "review until clean".
autolearn
Compound a solved problem into a durable in-repo learning doc. Use when a verified non-trivial fix lands, the user says "compound this", "document this fix", or "remember this". This is the automatic-capture entry point; for an explicitly requested one-off write-up, use compound.
doubt-driven
Doubt-driven adversarial review. Use when correctness matters more than speed, the code is unfamiliar, stakes are high, a claim can't be checked by the type system or compiler, or verifying now is cheaper than debugging later.
drift-detect
Use when the user says "plan drift", asks whether the roadmap, plans, or docs still match the code, or is deciding what to rebuild when restarting a stalled project. For doc-vs-code drift inside a specific diff, use sync-docs.