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 tmj-90/gaffer --skill frontend-forms-and-validationgit clone --depth 1 https://github.com/tmj-90/gafferWrote 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/tmj-90/gaffer/frontend-forms-and-validation)<a href="https://agentmods.dev/skills/tmj-90/gaffer/frontend-forms-and-validation"><img src="https://agentmods.dev/badge/skills/tmj-90/gaffer/frontend-forms-and-validation/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/tmj-90/gaffer/frontend-forms-and-validation"><img src="https://agentmods.dev/badge/skills/tmj-90/gaffer/frontend-forms-and-validation.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 | $0.00107 | $0.01573 |
| Opus 5.5 | $0.00043 | $0.00629 |
| Sonnet 5.5 | $0.00021 | $0.00315 |
| Haiku 4.5 | $0.00011 | $0.00157 |
Grade A, and why
frontend-forms-and-validation 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 16d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build a form that validates, explains and never loses input
A form is a contract with the server. Share the rules so client and server never disagree, tell the user what is wrong in text next to the field, keep every keystroke through errors and navigation, and make exactly one submission per intent. WCAG 2.2 AA criteria that apply directly: 1.3.1, 1.3.5 (autocomplete), 3.3.1, 3.3.2, 3.3.3, 3.3.4, 3.3.7 (redundant entry) and 3.3.8 (accessible authentication).
Steps
- Use the repo's form stack. The form library (React Hook Form, TanStack Form,
Formik, framework form actions, React 19
useActionState/useFormStatus), the schema library (Zod, Valibot, Yup) and the shared input components. Callsearch_lore; never add a second form or schema library. - One schema, both sides. Import or generate the schema the API validates with. The
client validates for speed; the server validates for truth (the
security-input-validationskill). Map the server's field errors (for example an RFC 9457 problem body with per-fielderrors) back onto the fields, and show form-level errors in the summary — never only in a toast. - Markup that assistive tech understands.
- Visible
<label for>on every control; placeholder is an example, never the label. - Groups of radios/checkboxes in
fieldset+legend. - Required marked in text ("required" or a legend explaining
*) plus therequiredattribute. - Help and error text linked by
aria-describedby;aria-invalid="true"only after the field has been validated and failed. autocompletetokens on personal data (name,email,tel,street-address,postal-code,cc-number,one-time-code,new-password,current-password) — required by 1.3.5 and it makes password managers work.- The right
type/inputmode/enterkeyhint(type="email",inputmode="numeric"for codes, nottype="number"for things that are not quantities).
- Visible
- Validate at the right moment. On blur for a field the user has left; on change once a field is showing an error (so it clears as they fix it); everything on submit. Never on the first keystroke. Async checks (username taken) are debounced and cancellable.
- On a failed submit: keep all input, show an error summary at the top with links to each field (the GOV.UK pattern), move focus to the summary (or to the only invalid field in short forms), and phrase each message as the fix: "Enter a date in the past", not "Invalid".
- Submit exactly once. While the request is pending: a visible pending state on the
button, repeated activations ignored, the request carries an idempotency key when the
API supports one (the
idempotency-and-retriesskill). Prefer ignoring re-clicks (oraria-disabled) over disabling the button before submission — a disabled submit hides why the form cannot be sent. After success: confirmation, then navigate or reset as the AC says. A failed submit that clears the form is a bug. - Editing existing records. Load the current value with its version/
ETag; submit it back. On409/412keep the user's edits and explain the record changed — do not silently overwrite another user's save (thefrontend-data-fetchingskill). - Preserve work. Multi-step flows keep earlier answers when the user goes back, and
never ask for the same information twice (3.3.7). Long forms keep a draft (per the
frontend-state-managementskill) and warn before leaving with unsaved changes. - Hard inputs. Dates: native
input type="date"or the design-system picker, stored as ISO 8601, displayed per locale (thei18n-l10nskill). Money: integer minor units plus currency code. Phone/postcode: lenient parsing, strict validation. Passwords and codes: allow paste and password managers, offer show-password, no cognitive-test CAPTCHA (3.3.8). Files: thefile-uploadsskill. - Test per AC (the
frontend-testingskill), withuserEventand the network mocked:- a valid submit sends the expected payload once and shows success;
- each rule the AC names shows its message, linked to the field
(
toHaveAccessibleDescription), andaria-invalidis set; - a server field error lands on the field; a 500 keeps all input and allows retry;
- double click / Enter twice → one request;
- the whole form is completable by keyboard, with fields found by label.
Evidence each AC with the
record-evidenceskill, then stop.
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.
- 16d ago Changed · +28 lines · +3 tokens per session a3515eb27ee2
- 19d ago First seen · 68 lines · 104 tokens per session scan A 52c5bc804374
frontend-forms-and-validation is a skill published in the GitHub repository tmj-90/gaffer (2 stars, last pushed 17d ago), licensed Apache-2.0. It adds 107 tokens to every session and 1,573 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-28.
Other skills, from other repositories
bulwark-brainstorm
Role-based brainstorming with dual modes: --scoped (sequential Task tool, 5 roles) and --exploratory (Agent Teams peer debate, 4 roles). Use for feasibility assessment and idea validation.
plan-creation
Create structured implementation plans via a 4-role scrum team (Product Owner, Architect, Eng/Delivery Lead, QA/Critic) with optional Agent Teams peer debate mode.
anthropic-validator
Validates Claude Code assets (skills, hooks, agents, commands, MCP servers, plugins) against official Anthropic standards. Fetches latest docs dynamically and produces structured validation reports.
create-subagent
Generates single-purpose Claude Code sub-agents for use via the Task tool. Use when creating dedicated sub-agents, scaffolding agent definitions, or generating agents with diagnostics and permissions setup.
test-audit
Audit test suites for T1-T4 violations using AST analysis, mock detection, and multi-stage synthesis. Invoke when user asks to audit tests, check test quality, find mock violations, review test effectiveness, or inspect test suites for over-mocking. Triggers automatic rewrites when quality gates fail.
code-review
Comprehensive code review with distinct aspect based sections. Use when reviewing code, checking for security issues, finding type safety problems, auditing code quality, or when user asks to review code, PRs or changes. Three-phase workflow runs static tools, LLM judgment, and writes diagnostic log.