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 cognitive-science-landscapegit 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/cognitive-science-landscape)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/cognitive-science-landscape"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/cognitive-science-landscape/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/cognitive-science-landscape"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/cognitive-science-landscape.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 | $0.00123 | $0.02047 |
| Opus 5 | $0.00062 | $0.01024 |
| Sonnet 5 | $0.00025 | $0.00409 |
| Haiku 4.5 | $0.00012 | $0.00205 |
Grade A, and why
cognitive-science-landscape 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 10d 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cognitive Science Landscape
Overview
Eight interconnected domains constitute human cognition: (1) Perception & Attention, (2) Memory, (3) Language & Thought, (4) Decision Making & Judgment, (5) Metacognition, (6) Emotion & Cognition, (7) Social Cognition, (8) Creativity & Innovation. Treating them in isolation produces local improvements systematically undermined by adjacent unaddressed weaknesses. The skill is NOT listing all eight domains — it is identifying which domain is the bottleneck and tracing its upstream dependencies.
Cross-skill composition: Use BEFORE [metacognition] (covers domain 5 of 8 only). Use WITH [cognitive-evolution-stages]: landscape = WHAT domains exist; evolution stages = how competence within any domain develops.
When to Use
- A cognitive intervention (memory training, decision frameworks, mindfulness) is not producing results
- Designing a learning or development program — avoid tunnel vision on one domain
- Communication failures, team problems, or leadership gaps with a cognitive origin
- Building AI systems that model or augment human cognition
- Someone says "think better" without specifying which domain is the bottleneck
When NOT to use: Domain already clearly identified (use domain-specific tools); problem is not cognitively rooted; immediate decision needed under time pressure.
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a concrete case → run The Process directly.
- Coach mode: user is unfamiliar or says "I want to think better" → 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.
- What it is: A map of 8 interconnected mental systems — locating your specific weakness lets us design an intervention that hits the right target.
- Check fit: Does your challenge involve memory, attention, decisions, self-monitoring, emotions, or social cognition? Which resonates?
- Elicit the real case: Walk me through the specific situation. What were you trying to do, and where did things go wrong?
[WAIT — do not advance until user responds]
- Domain identification first: Map the failure to a domain, then check which upstream domain may be causing it — don't jump to solutions.
[WAIT — do not advance until user responds]
- Name the payoff: Once we locate your bottleneck and its upstream dependencies, you'll have a targeted plan — six months of progress vs. six years.
[WAIT — do not advance until user responds]
What ships with it
2 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.
- 10d ago First seen · 121 lines · 123 tokens per session scan A d6cf0cf8a757
cognitive-science-landscape is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 8d ago), licensed MIT. It adds 123 tokens to every session and 2,047 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 2026-08-31.
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