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 deciqAI/knowledge-skills --skill okr-goal-settinggit clone --depth 1 https://github.com/deciqAI/knowledge-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/deciqai/knowledge-skills/okr-goal-setting)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/okr-goal-setting"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/okr-goal-setting/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/deciqai/knowledge-skills/okr-goal-setting"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/okr-goal-setting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00117 | $0.01888 |
| Opus 5 | $0.00059 | $0.00944 |
| Sonnet 5 | $0.00023 | $0.00378 |
| Haiku 4.5 | $0.00012 | $0.00189 |
Grade A, and why
okr-goal-setting 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OKRs (Objectives and Key Results)
Overview
OKRs separate ambition from measurement: an Objective is qualitative and aspirational; Key Results (3-5) are quantitative outcomes proving the objective was reached. KRs must be outcomes, not activities. Calibration rule: 70% achievement is success — routine 100% means goals were sandbagged. Developed by Andy Grove at Intel (1971); introduced to Google by John Doerr (1999).
Composes with north-star-metric, first-principles, metacognition, mece.
When to Use
- Team goals are vague, unmeasurable, or just "complete project X" lists
- Teams hitting all goals but the business isn't moving (sandbagging signal)
- Cross-team work failing due to private, conflicting goals; or a new company needs goal infrastructure
- Setting OKRs on AI features and the draft KR is "ship AI" / "increase AI usage" (vanity/Goodhart metric — replace with outcome KRs)
Not when: under ~10 people with sufficient informal alignment; inherently uncertain output (research labs); leadership will punish 70% achievement.
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a concrete case → run The Process directly.
- Coach mode: user unfamiliar or no concrete case → guide step by step.
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
- OKRs separate the inspirational what we're trying to be (Objective) from the measurable how we'll know (3-5 Key Results) — aiming for 70% so goals stretch beyond what's safe.
- Check fit: under 10 people / uncertain output / leadership punishes 70% → not the right time.
- Elicit the actual goal the team is trying to set.
[WAIT — do not advance until user responds]
- Ask one question at a time: what's the outcome? What would prove it happened? Activity or outcome? Would 70% be a real win?
[WAIT — do not advance until user responds]
- Close: one well-formed Objective and 3 Key Results, plus the cadence to revisit them.
[WAIT — do not advance until user responds]
What ships with it
4 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 · 117 lines · 117 tokens per session scan A 3b5abdb179f3
okr-goal-setting is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 117 tokens to every session and 1,888 once invoked, about $0.0006 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 2026-09-03.
Other skills, from other repositories
cro
Conversion audit for funnels and pages — a section-by-section friction log (clarity, anxiety, distraction, motivation), heuristic checks (message match, above-the-fold value prop, form cost), an ICE-scored hypothesis backlog, and top-3 A/B test designs with success metrics and minimum-sample notes. Use when the user…
prompt-master
Generates optimized prompts for AI tools. Activates only when the user explicitly asks to write, fix, improve, or adapt a prompt for a specific AI tool (LLM, Cursor, Midjourney, image AI, video AI, coding agents, etc.). Does not activate for general conversation, coding tasks, document writing, or other…
slack-tools
Slack workspace management and automation specialist.
syndic
Gère un parc de copropriétés en France avec vue portfolio consolidée. Couvre administration, comptabilité (décret 2005, plan comptable copro, 5 annexes), assemblées générales (convocation, PV, notification), appels de fonds, travaux, fournisseurs, recouvrement d'impayés et transition de syndic. Maîtrise les majorités…
ops-suggest
Show time-aware CocoOps operational suggestions from the deterministic ops-suggest classifier. Usage: $ops suggest.
customer-onboarding-and-implementation
Takes a new customer from signature to working — setting a definition of live that both sides agreed before the contract was signed, planning and staffing the implementation, running data migration and integration realistically, training the people who will actually use it, and handing over to the ongoing…