Borrowing it
Nothing to install: this file belongs to zkysar1/Claude-Mind. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zkysar1/Claude-Mind/main/.claude/skills/priority-review/SKILL.mdgit clone --depth 1 https://github.com/zkysar1/Claude-MindWrote 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/zkysar1/claude-mind/priority-review)<a href="https://agentmods.dev/skills/zkysar1/claude-mind/priority-review"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/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/zkysar1/claude-mind/priority-review"><img src="https://agentmods.dev/badge/skills/zkysar1/claude-mind/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 | $0.00091 | $0.02861 |
| Opus 5 | $0.00046 | $0.01430 |
| Sonnet 5 | $0.00018 | $0.00572 |
| Haiku 4.5 | $0.00009 | $0.00286 |
Grade A, and why
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 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 — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/priority-review — Aspiration Priority Dashboard
Shows all active aspirations ranked by aggregate goal score, and lets the user reorder priorities interactively. Closes the feedback loop between autonomous aspiration creation and user intent.
Hybrid skill: user-invocable AND agent-callable (from /respond). Valid from ANY state.
In reader mode: display only (no updates). In assistant/autonomous: full reordering.
Related: This is the user's anytime portfolio pull. See
.claude/skills/fresh-eyes-review/SKILL.md for the every-25-goals scheduled
push that asks the Self + portfolio meta-questions together. Priority
ranking changes flow naturally from either entry point.
Sub-commands
/priority-review — Show dashboard, accept reordering
/priority-review <user-input> — Process priority feedback directly (from /respond routing)
Phase 0: Load Conventions
Step 0: Load Conventions — Bash: load-conventions.sh with each name from the conventions: front matter. Read only the paths returned (files not yet in context). If output is empty, all conventions already loaded — proceed to next step.
Phase 1: Gather Data
1. World aspirations (shared queue — what all agents work on):
Bash: load-aspirations-compact.sh
IF path returned: Read the compact JSON
Extract all active aspirations with: id, title, priority, status, scope, source, tags, progress
2. Agent-local aspirations (this agent's private queue):
Bash: agent-aspirations-read.sh --active-compact
Extract active agent aspirations (maintenance, decomposed sub-goals)
3. Bash: goal-selector.sh select
Parse scored goal rankings to compute aggregate score per aspiration:
For each aspiration, sum the scores of its eligible (pending/in-progress) goals
Sort aspirations by: aggregate score (descending)
4. Read agents/<agent>/session/pending-questions.yaml
Check for any entries with type: "priority-review" AND status: "pending"
Note their IDs for Phase 4 consumption
5. OHS-delta rollup per aspiration (g-245-03)
Bash: meta-read.sh improvement-velocity.yaml
→ Parse YAML → velocity_map[goal_id] = ohs_delta_since_previous_ohs_run
→ For each aspiration, sum numeric deltas across its completed goals
→ ohs_delta_map[asp_id] = signed 2-decimal float OR "n/a" (when no numeric deltas)
→ Display: "+0.45" / "-0.12" / "n/a" (compact — reports are width-constrained)
→ Gracefully handle entries missing the field (pre-schema data) as 'no_ohs_data'
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 · 232 lines · 91 tokens per session scan A 561fbeaf7603
priority-review is a skill published in the GitHub repository zkysar1/Claude-Mind (5 stars, last pushed yesterday), licensed MIT. It adds 91 tokens to every session and 2,861 once invoked, about $0.0005 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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