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 maslow-hierarchygit 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/maslow-hierarchy)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/maslow-hierarchy"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/maslow-hierarchy/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/maslow-hierarchy"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/maslow-hierarchy.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 | $0.00110 | $0.01899 |
| Opus 5 | $0.00055 | $0.00949 |
| Sonnet 5 | $0.00022 | $0.00380 |
| Haiku 4.5 | $0.00011 | $0.00190 |
Grade A, and why
maslow-hierarchy 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Maslow's Hierarchy of Needs
Overview
Maslow's Hierarchy proposes needs organize into levels of prepotency — lower needs must be at least partially met before higher needs become motivationally dominant. Five levels: physiological → safety → love/belonging → esteem → self-actualization. The empirically supported insight is deficiency-dominance: severely unmet lower needs crowd out higher-level motivation. The strict sequential hierarchy is empirically weak (Wahba & Bridwell 1976; Tay & Diener 2011) — use as a diagnostic heuristic, not a strict theory. Supplement with Self-Determination Theory for high-stakes design.
Composes with jobs-to-be-done · okr-goal-setting · founder-mindset · principal-agent · pmf-crossing-the-chasm.
When to Use
- A motivation strategy (compensation, perks, career path) is being designed and isn't working
- An incentive that "should work" produces no engagement
- A product is being positioned and the underlying customer need is unclear
- A team can't engage with higher-order work because basic needs are unmet
- "Why isn't the bonus motivating them?" is being asked
- An AI strategy (AI capex push, AI adoption mandate, AI-native competition) triggers job-security fear that blocks engagement with the mission
Not when: formal motivational science is required; cross-cultural application is non-trivial; SDT fits better.
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a concrete motivation case → run The Process directly.
- Coach mode: user is unfamiliar or has 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.
- One-line: when an incentive isn't working, check whether lower-level needs (safety, security, belonging) are met first — higher-level rewards don't compensate for unmet basics.
- Check fit: if the situation requires precise motivation science, use SDT. Maslow is a diagnostic heuristic.
- Elicit the specific motivation situation: who is being motivated, with what, and why isn't it working?
[WAIT — do not advance until user responds]
- One question at a time: are physiological/safety needs met? Are belonging needs met? What level is the incentive targeting? What need is the person actually trying to meet?
[WAIT — do not advance until user responds]
- Close: matched-level intervention + acknowledgment of framework limits + plan to verify with direct conversation.
[WAIT — do not advance until user responds]
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.
- 9d ago First seen · 124 lines · 110 tokens per session scan A 9d265d774581
maslow-hierarchy is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 110 tokens to every session and 1,899 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.
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