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/madappgang/claude-code/patternsnpx skills add MadAppGang/claude-code --skill patternsgit clone --depth 1 https://github.com/MadAppGang/claude-codeWhat 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 | $0.00036 | $0.01532 |
| Opus 5 | $0.00018 | $0.00766 |
| Sonnet 5 | $0.00007 | $0.00306 |
| Haiku 4.5 | $0.00004 | $0.00153 |
Grade A, and why
patterns 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 — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
plugin: agentdev updated: 2026-02-11
Agent Patterns
External Model Invocation Pattern
External AI models are invoked via Bash+claudish CLI by the orchestrator (e.g., /team).
Agents do NOT need special blocks to support external models — the orchestrator calls
claudish directly:
# Orchestrator calls claudish directly via Bash tool
claudish --model {MODEL_ID} --stdin --quiet < prompt.md > result.md
This is 100% reliable because it's a deterministic CLI invocation, not a prompt-based delegation.
Tasks Integration Pattern
Every agent must track workflow progress.
<critical_constraints>
<tasks_requirement>
You MUST use Tasks to track your workflow.
**Before starting**, create task list:
1. Phase 1 description
2. Phase 2 description
3. Phase 3 description
**Update continuously**:
- Mark "in_progress" when starting
- Mark "completed" immediately after finishing
- Keep only ONE task "in_progress" at a time
</tasks_requirement>
</critical_constraints>
<workflow>
<phase number="1" name="Phase Name">
<step>Initialize Tasks with all phases</step>
<step>Mark PHASE 1 as in_progress</step>
<step>... perform work ...</step>
<step>Mark PHASE 1 as completed</step>
<step>Mark PHASE 2 as in_progress</step>
</phase>
</workflow>
Quality Checks Pattern (Implementers)
<implementation_standards>
<quality_checks mandatory="true">
Before presenting code, perform these checks in order:
<check name="formatting" order="1">
<tool>Biome.js</tool>
<command>bun run format</command>
<requirement>Must pass</requirement>
<on_failure>Fix and retry</on_failure>
</check>
<check name="linting" order="2">
<tool>Biome.js</tool>
<command>bun run lint</command>
<requirement>All errors resolved</requirement>
<on_failure>Fix errors, retry</on_failure>
</check>
<check name="type_checking" order="3">
<tool>TypeScript</tool>
<command>bun run typecheck</command>
<requirement>Zero type errors</requirement>
<on_failure>Resolve errors, retry</on_failure>
</check>
<check name="testing" order="4">
<tool>Vitest</tool>
<command>bun test</command>
<requirement>All tests pass</requirement>
<on_failure>Fix failing tests</on_failure>
</check>
</quality_checks>
</implementation_standards>
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 · 232 lines · 36 tokens per session scan A f271b7483364
patterns is a skill published in the GitHub repository MadAppGang/claude-code (279 stars, last pushed 5mo ago), licensed MIT. It adds 36 tokens to every session and 1,532 once invoked, about $0.0002 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 2026-08-30.
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