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 agentmods add skills/tupe12334/instinct/mecenpx skills add tupe12334/instinct --skill mecegit clone --depth 1 https://github.com/tupe12334/instinctWrote 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/tupe12334/instinct/mece)<a href="https://agentmods.dev/skills/tupe12334/instinct/mece"><img src="https://agentmods.dev/badge/skills/tupe12334/instinct/mece.svg" alt="Measured on agentmods" 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 | $0.00026 | $0.01772 |
| Opus 5 | $0.00013 | $0.00886 |
| Sonnet 5 | $0.00005 | $0.00354 |
| Haiku 4.5 | $0.00003 | $0.00177 |
Grade A, and why
mece 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 4d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MECE (Mutually Exclusive, Collectively Exhaustive)
Overview
MECE is a structuring principle from McKinsey used to break a problem or topic into categories that do not overlap (mutually exclusive) and together cover every possibility (collectively exhaustive). Apply it to issue trees, slide structures, research questions, and team responsibilities.
Topic: "Why are sales falling?"
BAD (overlaps + gaps) GOOD (MECE)
┌──────────────────┐ ┌──────────────────────┐
│ Marketing issues │ │ Volume (fewer deals) │
│ Bad marketing │ ← overlap│ Price (lower ASP) │← no overlap
│ Low pipeline │ │ Mix (cheaper SKUs) │
│ Economy │ ← gap: └──────────────────────┘
│ │ product? Revenue = Volume × Price × Mix
└──────────────────┘ covers all levers — no gaps
Core Concepts
Mutually Exclusive
Each item belongs to exactly one bucket. No item can logically fit in two categories at the same time. If two items can both claim the same fact, they overlap.
Collectively Exhaustive
The full set of items covers every possible case. No valid instance of the topic is left uncategorized. Ask: "Is there any scenario that falls outside all my buckets?" If yes — you have a gap.
Issue Tree
The main tool for applying MECE: a hierarchical breakdown where every level is MECE relative to its parent. Each node splits into children that are mutually exclusive and collectively exhaustive of that node.
Root question
├── Branch A (MECE siblings at level 1)
│ ├── A1 (MECE siblings at level 2)
│ └── A2
├── Branch B
│ ├── B1
│ └── B2
└── Branch C
How to Apply
Step 1 — State the root question precisely
Write the single question your structure must answer. Vague roots produce vague trees. "What should we do about revenue?" is weak; "Why did Q3 revenue miss forecast by 15%?" is sharp.
Step 2 — Choose a splitting logic
Pick one consistent dimension to split on at each level. Common logics:
- Mathematical identity: Revenue = Volume × Price × Mix
- Process/timeline: Discover → Evaluate → Purchase → Retain
- Organizational: By business unit, geography, or customer segment
- Causal: Internal vs. External; Supply vs. Demand
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.
- 4d ago First seen · 141 lines · 26 tokens per session scan A 072c75e202c1
mece is a skill published in the GitHub repository tupe12334/instinct (1 stars, last pushed 18d ago), licensed MIT. It adds 26 tokens to every session and 1,772 once invoked, about $0.0001 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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