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 DNYoussef/context-cascade --skill cognitive-modegit clone --depth 1 https://github.com/DNYoussef/context-cascadeWrote 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/dnyoussef/context-cascade/cognitive-mode)<a href="https://agentmods.dev/skills/dnyoussef/context-cascade/cognitive-mode"><img src="https://agentmods.dev/badge/skills/dnyoussef/context-cascade/cognitive-mode/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/dnyoussef/context-cascade/cognitive-mode"><img src="https://agentmods.dev/badge/skills/dnyoussef/context-cascade/cognitive-mode.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 | $0.00071 | $0.02245 |
| Opus 5.5 | $0.00028 | $0.00898 |
| Sonnet 5.5 | $0.00014 | $0.00449 |
| Haiku 4.5 | $0.00007 | $0.00225 |
Grade A, and why
cognitive-mode 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 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.
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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL-SPECIFIC GUIDANCE
When to Use This Skill
- Configuring cognitive modes for different task types (research, coding, security)
- Optimizing prompt engineering through GlobalMOO optimization
- Ensuring epistemic consistency with VERIX notation
- Selecting appropriate VERILINGUA cognitive frames
- Running multi-objective optimization on prompt configurations
- Meta-loop recursive improvement on foundry skills
When NOT to Use This Skill
- Simple one-off tasks that don't require specialized configuration
- Tasks where speed is paramount and optimization overhead is unacceptable
- When default balanced mode is sufficient
- Non-technical conversational interactions
Success Criteria
- Appropriate mode selected for task domain and complexity
- VERIX epistemic notation applied correctly to claims
- Cognitive frames activated match task requirements
- GlobalMOO optimization produces Pareto-optimal configurations
- Cross-model consistency maintained (Claude + Gemini + Codex)
Edge Cases & Limitations
- Mode selection may be uncertain for novel task types
- VERIX parsing may miss nuanced epistemic markers
- GlobalMOO optimization requires multiple iterations
- Some cognitive frames may conflict (e.g., minimal vs comprehensive)
Critical Guardrails
- NEVER skip VERIX grounding for high-confidence claims
- ALWAYS validate mode selection for security-sensitive tasks
- NEVER use minimal mode for compliance/audit tasks
- ALWAYS include confidence levels for factual assertions
- NEVER modify holdout corpus (never_optimize: true)
Evidence-Based Validation
- Mode selection validated against expected_metrics
- VERIX consistency checked via ConsistencyChecker
- Optimization results compared to Pareto frontier
- Cross-model evaluation via 3-model council
Cognitive Mode Management
A comprehensive skill for managing cognitive modes, VERILINGUA frames, VERIX epistemic notation, and GlobalMOO optimization in the Context Cascade plugin system.
Overview
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 · 270 lines · 71 tokens per session scan A 12a1dc825bdb
cognitive-mode is a skill published in the GitHub repository DNYoussef/context-cascade (32 stars, last pushed 3mo ago), licensed MIT. It adds 71 tokens to every session and 2,245 once invoked, about $0.0003 per session on Opus 5.5. 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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