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 pproenca/dot-skills --skill feature-arch-gategit clone --depth 1 https://github.com/pproenca/dot-skillsWrote 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/pproenca/dot-skills/feature-arch-gate)<a href="https://agentmods.dev/skills/pproenca/dot-skills/feature-arch-gate"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/feature-arch-gate/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/pproenca/dot-skills/feature-arch-gate"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/feature-arch-gate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00129 | $0.01362 |
| Opus 5 | $0.00064 | $0.00681 |
| Sonnet 5 | $0.00026 | $0.00272 |
| Haiku 4.5 | $0.00013 | $0.00136 |
Grade A, and why
feature-arch-gate 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 6d 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature-Arch Gate
Enforce React feature-based architecture conformance — a pass/fail gate: a single blind reviewer subagent judges the work against the rules of feature-arch v1.1.0 with an adversarial mandate, and the work passes only when every rule is PASS or N/A. This skill renders verdicts; it never fixes the work.
The gate is self-sufficient: the 33 decidable rules it enforces (of the source's 43) are vendored into this skill's references/ directory as a snapshot of feature-arch v1.1.0, so a review needs nothing outside this folder. references/_rule-evidence.md records the provenance, the evidence that decides each rule, and the 10 source rules excluded as non-decidable.
When to Apply
- A PR or branch touching a feature-organized React codebase needs an architecture conformance verdict before merge.
- A migration step from a
FEATURE-ARCH-TARGET.mdblueprint is claimed complete and needs independent verification. - A full
src/tree audit is requested ("does this codebase conform to feature-arch?"). - Agent-generated feature work needs a gate that is blind to the conversation that produced it.
Do NOT apply this gate to design or migrate an architecture — that is the feature-arch skill's job (it produces the blueprint; this skill judges conformance to the rules).
Review Protocol
Follow these steps exactly — the gate's value is that every review runs the same way.
- Identify the target. Pin down exactly what is under review (a diff, a set of files, or a full
src/tree) and note the ref/paths so the review runs against an unambiguous, fixed target. Record two context facts the reviewer needs: does the codebase use React Server Components, and is a query library (TanStack Query etc.) present — two rules are N/A without them. - Load the rules. Read references/_rule-evidence.md and resolve the 33 vendored rule files it lists against this skill's own
references/directory. If any listed rule file is missing or unreadable, STOP and report the error — never proceed with partial rules or silently pass. - Compose the reviewer prompt. Fill references/reviewer-prompt.md with the rule file paths, the target, and (if the target repo has one) its
docs/architecture/FEATURE-ARCH-TARGET.mdblueprint. The composed prompt must be fully self-contained — a reviewer sees no conversation history, so nothing may refer to context outside the prompt. - Dispatch one blind reviewer. Launch a single Task subagent whose entire input is the composed prompt — no conversation context, no commentary alongside it.
- Render fail-closed. The reviewer's structured output is the verdict — there is no merge step. Overall verdict is PASS only when every rule is PASS or N/A; any single FAIL fails the gate. Never average, weigh severity, or waive a rule — a "minor" FAIL is a FAIL.
- Render the verdict. Fill assets/templates/verdict.md. On FAIL, aggregate the reviewer's "missing for PASS" suggestions into the fix list, each with its location, ordered by the source skill's category priority (struct → import → bound → fquery → fcomp → fstate → test → name). Every rule whose final result is FAIL must appear in the fix list with a change concrete enough to apply as written — if the reviewer's suggestion only restates the violation, derive the fix from the rule's Correct example before rendering.
What ships with it
39 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/templates/verdict.md 1.5 KB
- gotchas.md 3.1 KB
- metadata.json 942 B
- references/_rule-evidence.md 8.6 KB
- references/_sections.md 2.0 KB
- references/bound-feature-scoped-routing.md 2.3 KB
- references/bound-interface-contracts.md 2.1 KB
- references/bound-minimize-shared-state.md 2.2 KB
- references/fcomp-colocate-styles.md 2.2 KB
- references/fcomp-composition-over-props.md 2.4 KB
- references/fcomp-error-boundaries.md 2.5 KB
- references/fquery-avoid-n-plus-one.md 2.3 KB
- references/fquery-colocate-with-feature.md 2.0 KB
- references/fquery-feature-scoped-keys.md 2.1 KB
- references/fquery-parallel-fetching.md 2.2 KB
- references/fquery-server-component-fetching.md 2.3 KB
- references/fquery-single-responsibility.md 2.0 KB
- references/fstate-feature-scoped-stores.md 2.2 KB
- references/fstate-server-state-separation.md 2.6 KB
- references/import-avoid-barrel-files.md 2.0 KB
- references/import-no-cross-feature.md 3.6 KB
- references/import-path-aliases.md 1.8 KB
- references/import-public-api.md 2.0 KB
- references/import-type-only.md 2.1 KB
- references/import-unidirectional-flow.md 2.2 KB
- references/name-descriptive-exports.md 2.0 KB
- references/name-feature-naming.md 2.7 KB
- references/name-file-conventions.md 2.8 KB
- references/reviewer-prompt.md 5.1 KB
- references/struct-app-layer.md 2.0 KB
- references/struct-feature-folders.md 2.1 KB
- references/struct-feature-self-contained.md 1.8 KB
- references/struct-flat-hierarchy.md 1.7 KB
- references/struct-optional-segments.md 2.4 KB
- references/struct-shared-layer.md 2.4 KB
- references/test-colocate-with-feature.md 2.0 KB
- references/test-feature-isolation.md 2.2 KB
- references/test-integration-at-app-layer.md 2.7 KB
- references/test-shared-utilities.md 2.5 KB
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.
- 6d ago First seen · 56 lines · 129 tokens per session scan A e464f41ea6e1
feature-arch-gate is a skill published in the GitHub repository pproenca/dot-skills (205 stars, last pushed 24d ago), licensed MIT. It adds 129 tokens to every session and 1,362 once invoked, about $0.0006 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 2026-09-03.
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