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/dikamilo/dx-workflow/dx-impl-reviewnpx skills add dikamilo/dx-workflow --skill dx-impl-reviewgit clone --depth 1 https://github.com/dikamilo/dx-workflowWrote 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/dikamilo/dx-workflow/dx-impl-review)<a href="https://agentmods.dev/skills/dikamilo/dx-workflow/dx-impl-review"><img src="https://agentmods.dev/badge/skills/dikamilo/dx-workflow/dx-impl-review.svg" alt="Measured on agentmods" 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 | $0.00025 | $0.01088 |
| Opus 5 | $0.00013 | $0.00544 |
| Sonnet 5 | $0.00005 | $0.00218 |
| Haiku 4.5 | $0.00003 | $0.00109 |
Grade A, and why
dx-impl-review 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 5d 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dx-impl-review
The post-implementation gate. Compare what was built against context/changes/<change-id>/plan.md and report — this skill reviews, it never fixes-and-hides the code it is checking. Findings land in a review file and on screen; the user decides what to do.
Guard. Resolve <change-id> under context/changes/. Missing → tell the user to run /dx-new. Under context/archive/ → refuse; an archived change is done. If plan.md's ## Progress still has a - [ ], the change isn't finished — say so and point at /dx-implement <change-id>.
1 — Load
Read plan.md fully (note change.md's type), its Standards to apply checklist and Priors & gotchas, and foundation/glossary.md (a one-line habit — review naming against the project's terms; if the diff's naming clashes with the glossary or reveals a term that only just resolved, invoke dx-domain). Get the diff scope: git log/git diff for the commits that landed this change's phases. Then invoke dx-references with knowledge-layer (how to verify standards compliance), with review-report (the finding-ID/Resolution schema and file convention shared with plan-review and review-triage), and — when type: refactor — also with module-design (depth/seam/deletion vocabulary for the pattern axis).
2 — Review on four dimensions
Fan out to built-in Explore/general-purpose subagents to keep the main context clean — e.g. one for drift, one for safety + standards. Each reads only the files it needs; don't pre-load 20 files here.
- Plan-drift — was what's in the diff what
plan.mdplanned? Flag intent mismatches, skipped items, and unplanned scope (extra files/behavior not in the plan). Ifplan.mdcarries any of the conditional sections (## Data model,## API & contracts,## Failure modes & reversibility), check the diff against what each one planned — a documented undo path or migration that the implementation never shipped is Plan-drift, not a new dimension. - Safety — data loss, destructive/irreversible ops, missing error handling at boundaries, hardcoded secrets, injection.
- Patterns — sound structure judged with the
module-designvocabulary (deep vs shallow, clean seams, does the interface leak?). Report substantive mismatches with sibling code, not style nits. - Standards compliance — did it follow the plan's matched Standards to apply? Cite the standard for each miss.
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.
- 5d ago First seen · 44 lines · 25 tokens per session scan A d112dbc18a51
dx-impl-review is a skill published in the GitHub repository dikamilo/dx-workflow (5 stars, last pushed 4d ago), licensed MIT. It adds 25 tokens to every session and 1,088 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
claude-md-improver
Audit and improve CLAUDE.md files in repositories. Use when user asks to check, audit, update, improve, or fix CLAUDE.md files. Scans for all CLAUDE.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CLAUDE.md maintenance" or "project…
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
gke-workload-security
Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running cluster security audits (auditcluster.sh), configuring Workload Identity Federation (impersonation, KSA/GSA binding, and pod setup), enforcing Network Policies (default-deny…
gke-reliability
Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for disaster recovery setup or full cluster backups (use gke-backup-dr instead).
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
google-cloud-solution-agentic-analytics-spark-knowledge-catalog
Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…