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/sequenzia/claude-plugins/project-conventionsnpx skills add sequenzia/claude-plugins --skill project-conventionsgit clone --depth 1 https://github.com/sequenzia/claude-pluginsWhat 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 | $0.00020 | $0.01500 |
| Opus 5 | $0.00010 | $0.00750 |
| Sonnet 5 | $0.00004 | $0.00300 |
| Haiku 4.5 | $0.00002 | $0.00150 |
Grade A, and why
project-conventions 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
91% identical to project-conventions — 5 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 — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Conventions
This skill guides you in discovering and applying project-specific conventions. Every codebase has its own patterns and practices - your job is to find them and follow them.
Convention Discovery Process
Step 1: Project Configuration
Check these files for explicit conventions:
Code Style:
.eslintrc*,eslint.config.*- JavaScript/TypeScript linting rules.prettierrc*,prettier.config.*- Formatting rulespyproject.toml,setup.cfg,.flake8- Python config.editorconfig- Editor settingsruff.toml,.ruff.toml- Ruff linter config
Project Structure:
tsconfig.json- TypeScript paths and settingspackage.json- Scripts, dependenciespyproject.toml- Python project config
Documentation:
CONTRIBUTING.md- Contribution guidelinesCLAUDE.md- AI coding guidelinesREADME.md- Project overviewdocs/- Extended documentation
Step 2: Existing Code Patterns
Study the codebase to find implicit conventions:
File Organization:
# Find how components are organized
ls -la src/components/
# Find test file patterns
find . -name "*.test.*" -o -name "*_test.*" -o -name "test_*"
# Find how utilities are organized
ls -la src/utils/ src/lib/ src/helpers/
Naming Patterns:
# Find function naming patterns
grep -r "^export function" src/ | head -20
grep -r "^def " src/ | head -20
# Find class naming patterns
grep -r "^export class" src/ | head -20
grep -r "^class " src/*.py | head -20
Import Patterns:
# Find import style (absolute vs relative)
grep -r "^import" src/ | head -30
grep -r "^from \." src/*.py | head -20
Step 3: Similar Features
Find features similar to what you're building:
-
Search for similar functionality:
# If building a "user profile" feature grep -r "profile" src/ find . -name "*profile*" -
Study the implementation:
- How is it structured?
- What patterns does it use?
- How does it handle errors?
- How is it tested?
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 · 271 lines · 20 tokens per session scan A 601584ef8ed3
project-conventions is a skill published in the GitHub repository sequenzia/claude-plugins (2 stars, last pushed 7mo ago), licensed MIT. It adds 20 tokens to every session and 1,500 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to project-conventions, differing in 5 lines, and is treated as a copy.
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