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 CodeInfinity1/Stram --skill focus-and-priority-reviewgit clone --depth 1 https://github.com/CodeInfinity1/StramWrote 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/codeinfinity1/stram/focus-and-priority-review)<a href="https://agentmods.dev/skills/codeinfinity1/stram/focus-and-priority-review"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/focus-and-priority-review/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/codeinfinity1/stram/focus-and-priority-review"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/focus-and-priority-review.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 | $0.00044 | $0.00604 |
| Opus 5.5 | $0.00018 | $0.00242 |
| Sonnet 5.5 | $0.00009 | $0.00121 |
| Haiku 4.5 | $0.00004 | $0.00060 |
Grade A, and why
focus-and-priority-review 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 1mo 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Focus And Priority Review
Purpose
Help the assistant and user choose the next best action from current evidence. This skill maps priority-review concepts to Stram's cognitive priority tools.
When To Use
Use when the user asks "what should I do next", "continue", "prioritize this", "what is important", or when autonomous work needs a bounded next action.
Inputs And Evidence
- Active goals, tasks, and focus from
cognitive_state. - Commitments, wakeups, and recent briefings.
- Environment constraints and current system status.
- User urgency, deadlines, and interruption tolerance.
Tool Map
cognitive_priority_reviewcognitive_priority_statuscognitive_statecognitive_environment_statuscognitive_commitment_statusautomation_daemon_tick
Workflow
- Gather active work and explicit user constraints.
- Identify hard deadlines, blockers, dependencies, and high-risk unresolved items.
- Ask the model to rank next actions from evidence instead of task title similarity.
- Choose one primary focus and at most a few secondary items.
- If autonomous mode is active, queue only one interruptible next action unless explicitly allowed.
- Communicate the reasoning and what will be deferred.
Safety And Boundaries
- Do not bury user-explicit priorities under inferred priorities.
- Do not trigger high-risk work without approval.
- Do not keep cycling priority reviews when the next action is already clear.
Safety And Approval
- Priority review can recommend work, but it cannot authorize high-risk tools, external-visible actions, or durable state changes by itself.
- Preserve explicit user priorities over inferred urgency unless current evidence shows a blocker or safety issue.
- Do not queue autonomous work unless the user allowed initiative or the active goal requires bounded continuation.
- Avoid repeated priority loops that consume time without creating a concrete next action.
Native Implementation Boundaries
- Use Stram priority review/status, cognitive state, environment, commitment, and automation daemon tools.
- The model ranks actions from evidence; deterministic code must not rank by recency, keyword, or static urgency lists.
- Queue/status changes must be visible in native records before claiming the assistant will act later.
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.
- 1mo ago First seen · 76 lines · 44 tokens per session scan A cd095026183d
focus-and-priority-review is a skill published in the GitHub repository CodeInfinity1/Stram (11 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 604 once invoked, about $0.0002 per session on Opus 5.5. 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 skills, from other repositories
ask-agents
Send a task or question to Claude Code and/or Gemini as external subagents and report back what they said. Use when the user asks to ask Claude, ask Gemini, ask both, get a second opinion, split reviewer roles, or compare external agents.
review-plan
Review a proposed plan with a single-pass structured critique and a clear verdict. Use when the user asks to review a plan, stress-test a plan, critique a workflow, identify risks, or improve an execution sequence.
alive:settings
The human wants to adjust how the system behaves — not what it contains, but how it feels. Voice, rhythm, preferences, walnut-level config, full permissions toggleable, named squirrel config, action logging toggle. The system adapting to them. Routes to preferences.yaml or walnut config.yaml depending on scope. For…
lark-contact
A Feishu (Lark) contacts tool for finding users or bots and looking up their profiles and contact details.
oci-services-expert
Expert guidance on Oracle Cloud Infrastructure services, architecture patterns, cost optimization, and deployment strategies. Use when designing on OCI, selecting OCI services, estimating cost, or applying OCI enterprise best practices.
openai-agentkit
Build production multi-agent systems with OpenAI AgentKit and the Agents SDK — orchestration, handoffs, and routines. Use when writing agents against OpenAI's AgentKit/Agents SDK or porting an agent design to the OpenAI stack.