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.
git clone --depth 1 https://github.com/HoangNguyen0403/agent-skills-standardWrote 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/commands/hoangnguyen0403/agent-skills-standard/implementation-readiness)<a href="https://agentmods.dev/commands/hoangnguyen0403/agent-skills-standard/implementation-readiness"><img src="https://agentmods.dev/badge/commands/hoangnguyen0403/agent-skills-standard/implementation-readiness/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/commands/hoangnguyen0403/agent-skills-standard/implementation-readiness"><img src="https://agentmods.dev/badge/commands/hoangnguyen0403/agent-skills-standard/implementation-readiness.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 | $0.00000 | $0.00768 |
| Opus 5 | $0.00000 | $0.00384 |
| Sonnet 5 | $0.00000 | $0.00154 |
| Haiku 4.5 | $0.00000 | $0.00077 |
Grade A, and why
implementation-readiness 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 8d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Readiness
Verify BRD-lite, PRD, SRS/FRS, UX, and test prerequisites before implementation starts.
Input: $ARGUMENTS
Optional args: slug=, ticket=<id/url>, mode=interactive|autonomous|channel, channel=, auto_continue=true|false, profile=business|hybrid|technical.
Instructions
Execute the following steps for $ARGUMENTS.
Implementation Readiness Workflow
Goal: Decide whether a planned change is ready for implementation or must return to planning/design.
Steps
-
Load artifacts:
- BRD-lite brief, PRD/story, SRS/FRS notes, UX/design links, implementation plan, test plan.
- Jira/GitHub/GitLab/ADO/Figma/Confluence MCP context when configured; otherwise use exported docs or local files.
-
Check readiness:
- BRD-lite has business goal, stakeholder, AS-IS to TO-BE, and measurable success metric.
- ACs atomic, testable, scoped by platform/market/role where relevant.
- PRD has stable requirement IDs, AC IDs, owner, priority, status, and last-updated note.
- SRS/FRS identifies touched modules, API/data/interface changes, migrations, permissions, failure modes, and NFR thresholds.
- Requirement trace is complete: BRD objective -> PRD requirement -> SRS/FRS contract -> test lane.
- UX/design states cover loading, empty, error, permission, and responsive/mobile cases when UI changes.
- Test strategy maps ACs to unit, integration, E2E/mobile, security, and Zephyr/manual coverage.
- Tool prerequisites known: credentials, environments, feature flags, test data, MCP availability.
-
Decide:
- READY: BA/PM/SRS/test prerequisites are present and implementation can start.
- BLOCKED: missing artifact, owner, unclear AC, missing design/architecture, unavailable environment, or unresolved risk.
- PARTIAL: only named slices can start; blocked slices have explicit owner/input.
-
Route:
- For autonomous/channel mode, return READY only with named slices, owners, verification lanes, and available environments.
- READY ->
implement-featureordev-fix. - BLOCKED ->
plan-featureordesign-solution. - PARTIAL -> slice task list plus blockers.
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.
- 8d ago First seen · 79 lines · 0 tokens per session scan A cb7ff31757bc
implementation-readiness is a command published in the GitHub repository HoangNguyen0403/agent-skills-standard (565 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 768 tokens. 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.
Other commands, from other repositories
debug
Structured bug diagnosis and fixing workflow that reproduces, diagnoses root cause, applies a minimal fix, writes regression tests, and scans for similar patterns.
journey-test
The /journey-test command turns a project description into a coherent user journey test plan (TESTPLAN-NNN.md) plus matching E2E skeletons, so a new project has a complete, ordered test journey from day one.
e2e
An end-to-end testing assistant for guiding tests that exercise a complete user flow across an application. E2E tests check the system as a user would use it, rather than checking one small part in isolation.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.