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 serejaris/personal-corp-os --skill pm-prioritizegit clone --depth 1 https://github.com/serejaris/personal-corp-osWrote 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/serejaris/personal-corp-os/pm-prioritize)<a href="https://agentmods.dev/skills/serejaris/personal-corp-os/pm-prioritize"><img src="https://agentmods.dev/badge/skills/serejaris/personal-corp-os/pm-prioritize/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/serejaris/personal-corp-os/pm-prioritize"><img src="https://agentmods.dev/badge/skills/serejaris/personal-corp-os/pm-prioritize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00140 | $0.02396 |
| Opus 5 | $0.00070 | $0.01198 |
| Sonnet 5 | $0.00028 | $0.00479 |
| Haiku 4.5 | $0.00014 | $0.00240 |
Grade A, and why
pm-prioritize 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 11d 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 — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pm-prioritize — Rank requirements with RICE / ICE / MoSCoW / Kano
Part of the Personal Corp framework — running a one-person business through AI agents.
Rank a list of requirements using a structured framework. A built-in decision tree picks the right framework based on data availability and decision context. Output is transparent and traceable, so a team can argue with the scores instead of the recommendation.
Inputs
| Field | Required | Notes |
|---|---|---|
| Requirement list | yes | Name + brief description; ≥ 3 items. Can take a pain-point list from /pm-feedback or a feature list from /pm-prd |
| Framework | no | RICE / ICE / MoSCoW / Kano; auto-recommended if not given |
| Business goal | no | Current focus (growth / retention / revenue / efficiency); affects weighting |
| Resource constraint | no | Available dev capacity (person-days or Story Points) |
Optional config
Most of the skill works out-of-box. If you want stable defaults across runs, add an ## Prioritize Config section to your project's CLAUDE.md:
## Prioritize Config
### Default framework (optional)
If unset, the skill auto-recommends per the decision table below.
- default_framework: RICE | ICE | MoSCoW | Kano
### Default resource constraint (optional)
Used in the Sprint allocation step. Skip if you'd rather state it per run.
- sprint_capacity: 20 person-days per Sprint
### Backlog source (optional)
Where the skill should fetch the requirement list from when you don't paste one.
- backlog_source: gh-issues # gh-issues | github-project | tasks-file | paste
- gh_owner: your-github-handle
- gh_repo: your-main-repo
- gh_label: backlog
- tasks_file: docs/backlog.md
When a config field is set, the skill uses it silently. When unset, the skill asks (see "When input is incomplete").
Research commands (auto-discovery)
If the user points at a backlog source instead of pasting items, the skill can pull the list itself:
# GitHub issues by label
gh issue list -R $OWNER/$REPO --label $LABEL --state open \
--json number,title,body --limit 100
# GitHub Project items
gh project item-list $PROJECT_ID --owner $OWNER --format json
# Local backlog file
cat $TASKS_FILE
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.
- 11d ago First seen · 192 lines · 140 tokens per session scan A 4035d7646be5
pm-prioritize is a skill published in the GitHub repository serejaris/personal-corp-os (225 stars, last pushed 15d ago), licensed MIT. It adds 140 tokens to every session and 2,396 once invoked, about $0.0007 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.
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