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/woopnpx skills add tupe12334/instinct --skill woopgit clone --depth 1 https://github.com/tupe12334/instinctWhat 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 | $0.00021 | $0.01704 |
| Opus 5 | $0.00010 | $0.00852 |
| Sonnet 5 | $0.00004 | $0.00341 |
| Haiku 4.5 | $0.00002 | $0.00170 |
Grade A, and why
woop 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 yesterday.
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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WOOP
Overview
WOOP is a science-backed goal-setting method developed by psychologist Gabriele Oettingen. It uses mental contrasting — imagining the best outcome AND the realistic obstacles together — then anchors action with an if-then plan. Pure positive thinking increases wishful daydreaming but lowers effort; WOOP short-circuits that by forcing obstacle acknowledgment upfront.
WISH OUTCOME OBSTACLE PLAN
───── ──────── ────────── ──────────────────
What do → Best result → Inner block → If [obstacle],
I want? if it works? standing then I will
in the way [specific action]
Elements
W — Wish
A meaningful, challenging but realistic desire. The wish should stretch you but not be fantasy. Too easy = no motivation. Impossible = hopeless paralysis.
- Frame it in 3–6 words: "Launch product by Q3", "Run a 10K", "Ship the API rewrite"
- It must be something you genuinely want, not something you feel you should want
- Scope it to a single goal; do not bundle multiple wishes
O — Outcome
The single best result of fulfilling the wish. Visualize it vividly and specifically — what does success look, feel, and mean? This is not a list of benefits; it is one concrete peak moment or state.
- Bad: "I'll feel good about myself"
- Good: "The product is live, the first paying customer signs up, and the team celebrates"
- Spend 1–2 minutes actually picturing this in your mind before moving on
O — Obstacle
The primary inner obstacle — a habit, emotion, assumption, or behavior pattern — that could prevent you from reaching the outcome. This is not an external blocker (budget cuts, other people). It is something within you.
- Bad obstacle: "My manager doesn't give me time" (external)
- Good obstacle: "I procrastinate when tasks feel ambiguous" (internal)
- Pick the single most critical obstacle; do not list five
P — Plan
An if-then implementation intention tied directly to the obstacle. The format is strict: "If [obstacle occurs], then I will [concrete behavior]."
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.
- yesterday First seen · 118 lines · 21 tokens per session scan A 4700680455bc
woop is a skill published in the GitHub repository tupe12334/instinct (1 stars, last pushed 16d ago), licensed MIT. It adds 21 tokens to every session and 1,704 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.
Other skills, from other repositories
thinking-model-router
When unsure which thinking skill fits, map domain and problem type, then return NONE or one primary skill by default (at most three complementary).
thinking-opportunity-cost
Before committing scarce time, people, or money, name the best forgone use of those resources and the value delta of the chosen path versus that alternative.
thinking-red-team
For authorized security review of code, auth, or APIs you control, model the attacker, map the attack surface, and report only findings with a reproducible exploit path and verified mitigation.
thinking-scientific-method
When a symptom has several plausible causes, rank falsifiable hypotheses and run the cheapest discriminating observation first; prefer least-assumptive survivors only after evidence fit.
thinking-systems
When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.
thinking-circle-of-competence
Use when a specific claim may lack grounding. Check evidence boundary, size wrongness cost, then answer, fetch, or abstain — never confabulate.