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/pdcanpx skills add tupe12334/instinct --skill pdcagit 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 | $0.00017 | $0.01862 |
| Opus 5 | $0.00009 | $0.00931 |
| Sonnet 5 | $0.00003 | $0.00372 |
| Haiku 4.5 | $0.00002 | $0.00186 |
Grade A, and why
pdca 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 2d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDCA Cycle (Plan–Do–Check–Act)
Overview
PDCA is a four-phase iterative loop for solving problems and improving processes. Each cycle produces a tested change; repeat until the target condition is reached. Also called the Deming Wheel or Shewhart Cycle.
┌─────────────────────────────┐
│ │
┌────▼────┐ ┌────────┴────┐
│ PLAN │ │ ACT │
│ Define │ │ Standardize │
│ target │ │ or re-plan │
└────┬────┘ └────────▲────┘
│ │
┌────▼────┐ ┌────────┴────┐
│ DO │──────────────►│ CHECK │
│ Execute │ │ Measure & │
│ on small│ │ compare │
│ scale │ └─────────────┘
└─────────┘
PDCA is most effective on measurable, repeatable processes — defect rates, cycle times, conversion rates, error counts.
Phase Definitions
Plan — Identify the gap and design a countermeasure
- State the problem in measurable terms: current value vs. target value.
- Root-cause analysis before jumping to solutions (use Five Whys or fishbone if needed).
- Define one hypothesis: "If we change X, we expect Y to improve by Z."
- Specify success criteria, measurement method, and timeline up front.
Do — Execute the change at small scale
- Run a controlled pilot or time-boxed experiment — not a full rollout.
- Keep scope small enough to be reversible in hours or days.
- Document what was done, who did it, and any deviations from the plan.
- Collect raw data during execution — do not rely on memory after the fact.
Check — Compare results to the prediction
- Measure the same metric(s) defined in Plan.
- Did results match the hypothesis? If not, why?
- Separate signal from noise: was the sample size or duration enough to draw a conclusion?
- List side effects — unintended changes to adjacent metrics.
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.
- 2d ago First seen · 131 lines · 17 tokens per session scan A ab145340ff3e
pdca is a skill published in the GitHub repository tupe12334/instinct (1 stars, last pushed 16d ago), licensed MIT. It adds 17 tokens to every session and 1,862 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-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.
thinking-five-whys-plus
When a fault is localized and the proximate cause is known but the systemic root is not, chain evidence-linked whys with a counterfactual stop and a countermeasure.