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 skills add s977043/river-review --skill skill-ops-plannergit clone --depth 1 https://github.com/s977043/river-reviewWrote 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/s977043/river-review/skill-ops-planner)<a href="https://agentmods.dev/skills/s977043/river-review/skill-ops-planner"><img src="https://agentmods.dev/badge/skills/s977043/river-review/skill-ops-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/skills/s977043/river-review/skill-ops-planner"><img src="https://agentmods.dev/badge/skills/s977043/river-review/skill-ops-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 | $0.00087 | $0.00979 |
| Opus 5 | $0.00044 | $0.00490 |
| Sonnet 5 | $0.00017 | $0.00196 |
| Haiku 4.5 | $0.00009 | $0.00098 |
Grade A, and why
skill-ops-planner 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 9d 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pattern declaration
Primary pattern: Pipeline Secondary patterns: Reviewer, Inversion Why: portfolio planning requires strict phase order (inventory → classify → policy → metrics → roadmap) with review checkpoints at each stage. Inversion is needed at Phase 0 to block progress when inventory data is insufficient.
Purpose
Plan how a team should operate a set of skills over time.
Your job is to define:
- portfolio structure
- ownership
- lifecycle stages
- evaluation policy
- rollout policy
- retirement policy
- review cadence
Phase 0: Portfolio gate
Before planning, identify:
- active skills
- target users or teams
- current pain points
- risk level by skill category
- current review process
- current storage layout
- current evaluation maturity
If any of the above cannot be determined:
- stop and ask the user for the missing information
- do not proceed to Phase 1 until at least active skills and current storage layout are confirmed
- if no inventory exists at all, output an inventory-first plan and stop
Phase 1: Inventory and pattern segmentation
For each skill, record:
- owner
- purpose
- invocation policy (auto vs manual)
- risk level
- primary pattern (Tool Wrapper / Generator / Reviewer / Inversion / Pipeline)
- secondary patterns
- current eval maturity
- review requirement
Output each skill as a structured record:
skill: <name>
owner: <person or team>
purpose: <one line>
invocation: auto | manual
risk: low | medium | high
primary_pattern: <pattern>
secondary_patterns: <patterns or none>
eval_maturity: none | basic | comprehensive
review: <cadence>
Then group the portfolio by:
- responsibility type (knowledge / workflow / investigation / review / operational)
- risk type
- design pattern
Phase 2: Lifecycle policy
Define lifecycle stages:
- proposed
- experimental
- team-approved
- production
- deprecated
- retired
For each stage, define:
- entry criteria
- required eval coverage
- review requirement
- allowed blast radius
- logging requirement
- retirement signals (when to deprecate or retire)
What ships with it
3 files 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.
- 9d ago First seen · 199 lines · 87 tokens per session scan A d55a45048358
skill-ops-planner is a skill published in the GitHub repository s977043/river-review (3 stars, last pushed today), licensed MIT. It adds 87 tokens to every session and 979 once invoked, about $0.0004 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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