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 arozumenko/sdlc-skills --skill prioritize-betsgit clone --depth 1 https://github.com/arozumenko/sdlc-skillsWrote 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/arozumenko/sdlc-skills/prioritize-bets)<a href="https://agentmods.dev/skills/arozumenko/sdlc-skills/prioritize-bets"><img src="https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/prioritize-bets/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/arozumenko/sdlc-skills/prioritize-bets"><img src="https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/prioritize-bets.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 | $0.00193 | $0.02987 |
| Opus 5.5 | $0.00077 | $0.01195 |
| Sonnet 5.5 | $0.00039 | $0.00597 |
| Haiku 4.5 | $0.00019 | $0.00299 |
Grade C, and why
prioritize-bets scanned grade C with 1 finding 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.
Tells the agent never to refusehighAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
the warning: the ordering is honest about being a guess. Never refuse to rank — the PO may How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
prioritize-bets
The ranking skill. It answers "which of these validated bets comes first?" — the question the promotion gate never asks. A promotion gate tells you a hypothesis may proceed; it never tells you in what order. When more bets clear the gate than the team's appetite can build, this skill turns the backlog into a defensible ordered list and writes the ranks where they survive the session.
The load-bearing rule: a RICE or ICE score cannot exist without its evidence class. RICE's (and ICE's)
confidence factor is not a number the PO types in — it is derived from the hypothesis's
own evidence-banded confidence: block. Prioritization therefore consumes the validation
pipeline instead of vibes: a bet nobody has validated cannot borrow a high confidence to jump
the queue. Every persisted score carries an evidence_note naming the dimensions and band it
came from, so the ranking is auditable.
What this skill reads (config, by name)
From .agents/profile.md, if it carries a prioritization: note:
- the active
framework:(RICE | WSJF | ICE) and its scales: the RICEimpact_scale(massive:3 high:2 medium:1 low:0.5 minimal:0.25),reach_unit,effort_unit; the WSJF cost-of-delay components and job-size unit; the ICE scales. The framework and its numbers live in the profile note, never hardcoded in this skill — change the note and the math changes. If.agents/profile.mdcarries noprioritization:note (or the note doesn't exist), default to RICE with the default scales documented inreferences/frameworks.md, and say plainly that the default is in effect. - a
staleness_daysvalue, if the note carries one: a persistedscored_onolder than this is what a later status/review pass would flag as stale. This skill writes the stamp that such a check would read; it does not itself audit staleness.
From .agents/profile.md and the project's docs/, more broadly: the product one-liner and
stakeholder cast, so a reach estimate names a real customer count rather than an invented one.
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.
- 1mo ago First seen · 183 lines · 193 tokens per session scan C 2b47a39beebc
prioritize-bets is a skill published in the GitHub repository arozumenko/sdlc-skills (25 stars, last pushed yesterday), licensed MIT. It adds 193 tokens to every session and 2,987 once invoked, about $0.0008 per session on Opus 5.5. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
story-readiness
Checks whether a story is ready to implement: clear acceptance criteria, no open questions, valid ADR and dependencies. Use when the user asks if a story, or the sprint's stories, are ready to start or build.
recipe-create-meet-space
Create a Google Meet meeting space and share the join link.
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
qa-project-bootstrap
Onboard a new QA engineer to an existing codebase, or audit an existing test architecture. Produces a 30-day ramp plan: codebase orientation, framework walkthrough, test architecture audit, mentorship pairing, and first-test guidance. Use when: "QA onboarding," "new tester," "ramp up," "test architecture audit,"…
handle-linkedin-connection-request-signal
Use this skill when someone sends a team member an inbound LinkedIn connection request. An inbound request is a deliberate, ACTIVE first-party intent signal — meaningfully stronger than a passive profile view — and it deserves different scoring rules. The skill resolves and enriches the requester, gates them through…