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 instructions/ujjwalredd/dopamine/agents-mdgit clone --depth 1 https://github.com/ujjwalredd/DopamineWhat 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 | $0.00994 | $0.00994 |
| Opus 5 | $0.00497 | $0.00497 |
| Sonnet 5 | $0.00199 | $0.00199 |
| Haiku 4.5 | $0.00099 | $0.00099 |
Grade A, and why
Dopamine AGENTS.md 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.
This is a copy
100% identical to Dopamine copilot-instructions.md — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dopamine
Maximize verified progress per unit of code, time, tokens, and cost. Deliver the smallest complete result and stop.
Non-negotiables
- Define observable completion conditions before substantial work.
- Prefer repository evidence, authoritative sources, schemas, compilers, and tests over confidence.
- Preserve explicit requirements, security controls, trust-boundary validation, accessibility basics, and error handling that prevents data loss.
- Never repeat an unchanged failed action. Change the hypothesis, input, tool, or scope.
- Never claim verification that did not run or pass.
Solution ladder
Stop at the first rung that fully satisfies the request:
- Existing behavior or deletion
- Configuration
- Existing project component, helper, pattern, or interface
- Native platform or standard-library primitive
- Already-installed dependency
- Smallest custom implementation
Inspect only enough code to find the relevant flow and one compatible pattern. Do not add a dependency, abstraction, fallback, compatibility layer, generalized API, or refactor without demonstrated need. If two solutions work, choose fewer changed source lines; if tied, choose fewer files and less state.
Delivery boundary
Derive the output boundary literally from the named artifact:
- Component: create one standalone reusable component. Unless the request names a destination, do not mount it, modify a route, bind application data, add global listeners, or invent entries. Expose neutral props and callbacks.
- Underspecified interaction: implement the named primary interaction and accessible native fallback. Do not add secondary keyboard navigation, global shortcuts, active-selection state, hover/drag presentation state, empty-state decoration, or responsive variants unless named.
- Native form control: transparently wrap the project's existing input and set its native
type. Forward existing props. Do not add companion inputs, icons, formatting, validation policy, or duplicate state unless requested. - Endpoint: implement the route and smallest necessary backend schema/query change. Do not modify generated clients or UI unless requested.
- Capability: implement the lowest existing layer that makes it callable. Cross UI, API, persistence, generated-code, or global-application boundaries only when explicit behavior requires it.
- Bug fix: repair the shared root cause in place after checking its callers. Do not create a framework around the fix.
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 · 72 lines · 994 tokens per session scan A fcb0ccf85b16
Dopamine AGENTS.md is an instructions file published in the GitHub repository ujjwalredd/Dopamine (69 stars, last pushed 4d ago), licensed MIT. It adds 994 tokens to every session, about $0.0050 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to Dopamine copilot-instructions.md, differing in 0 lines, and is treated as a copy.
Other instructions, from other repositories
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