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 skills add gosha70/code-copilot-team --skill coding-standardsgit clone --depth 1 https://github.com/gosha70/code-copilot-teamWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gosha70/code-copilot-team/coding-standards)<a href="https://agentmods.dev/skills/gosha70/code-copilot-team/coding-standards"><img src="https://agentmods.dev/badge/skills/gosha70/code-copilot-team/coding-standards/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gosha70/code-copilot-team/coding-standards"><img src="https://agentmods.dev/badge/skills/gosha70/code-copilot-team/coding-standards.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00027 | $0.01041 |
| Opus 5.5 | $0.00011 | $0.00416 |
| Sonnet 5.5 | $0.00005 | $0.00208 |
| Haiku 4.5 | $0.00003 | $0.00104 |
Grade A, and why
coding-standards scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Execute your own test plan.** If you write test commands (curl, bash, docker, etc.) as part of a build summary, run every command yourself and report results before declaring done. How it starts
The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Coding Standards
Applied to all code generation and review sessions.
Quality Gates (enforce before merge/commit)
- Lint errors: 0
- Test coverage: >= 80% (critical paths >= 95%)
- No commented-out code
- No unused imports or dead code
- No hard-coded secrets or credentials
Prohibited Patterns
- No hard-coded structured data (JSON/XML literals) inside source — use config files or env vars. This includes default values on Python dataclasses/Pydantic models and equivalents in other languages — define only the schema in code; put actual defaults in
config/defaults.yaml(or equivalent). A config loader reads the file and populates the schema; env vars or override files layer on top. - No magic numbers or strings — use named constants. When a string key crosses a module boundary (config key, variable name, prompt template name), define it as a constant in the lowest common ancestor package and import it everywhere. A hardcoded string in two modules is a silent breakage waiting to happen.
- No secrets in source — use env vars or a secrets manager.
- No print() debugging in committed code — use structured logging.
- No wildcard imports.
- No bare except / catch without specific exception types.
- No SQL string concatenation — use parameterized queries.
Verification Discipline
- Never suggest skipping a failing verification step. When a test, build, lint check, Docker build, or script execution fails, diagnose and fix the issue. Do not suggest workarounds that bypass the deliverable.
- Execute your own test plan. If you write test commands (curl, bash, docker, etc.) as part of a build summary, run every command yourself and report results before declaring done.
- Build it, run it. Any executable artifact you create (Dockerfile, shell script, CI workflow, launcher flag) must be executed at least once before committing. Syntax validity alone is not sufficient.
- Re-review after fix. After applying a fix for a bug flagged in code review or a reviewer note, run the review process again (e.g.,
/team-reviewor the equivalent specialist agent) before declaring done. Do not just apply the fix and move on — the re-review may catch secondary issues exposed by the fix itself. - Confirm against origin before declaring done. Run
scripts/check-origin-alignment.sh <feature-id>before presenting any feature for review. Exit ≥ 2 means the working artifact has drifted from the user's origin and you must surface the three-resolution escalation (rescope / restart / document divergence) — do not proceed. Seeshared/skills/origin-confirmation/SKILL.mdfor the full protocol.
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.
- 1mo ago First seen · 50 lines · 27 tokens per session scan A 4cb10ae09ec8
coding-standards is a skill published in the GitHub repository gosha70/code-copilot-team (7 stars, last pushed 17d ago), licensed MIT. It adds 27 tokens to every session and 1,041 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
pipeline-efficiency-benchmark
A repeatable benchmark for comparing different versions of a development pipeline. It runs the same public tasks in isolated workspaces and records scores, tokens, time, tool calls, and cost.
x-qdev
A compact development workflow for a small, clearly defined code change. It keeps the requirement, initially failing tests, implementation, and real verification results in one task document, following TDD, or test-driven development.
x-verify-tech
A technical acceptance check for comparing implemented code with an approved technical design and the project's development rules. It extracts the design constraints, examines the relevant code, and reports what passed, failed, or was not verified.
x-adversarial-risk
A focused adversarial review of a software specification. It tries to find small counterexamples that would expose incorrect implementations, such as invalid state changes, crashes, duplicate actions, permission mistakes, or concurrent events.
x-qa-gate
A quality-review gate for completed development tasks. It checks the code against the request, design, tests, verification evidence, and current changes, using different review rounds for different risk levels.
x-verify
A fact-checking gate that reruns the automated checks listed for a development task and reports which checks passed, failed, or still need a person. It is one step in a larger development process.