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/NVZver/claude-marketplaceWrote 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/nvzver/claude-marketplace/prompt-review)<a href="https://agentmods.dev/commands/nvzver/claude-marketplace/prompt-review"><img src="https://agentmods.dev/badge/commands/nvzver/claude-marketplace/prompt-review/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/nvzver/claude-marketplace/prompt-review"><img src="https://agentmods.dev/badge/commands/nvzver/claude-marketplace/prompt-review.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 | $0.00022 | $0.01076 |
| Opus 5 | $0.00011 | $0.00538 |
| Sonnet 5 | $0.00004 | $0.00215 |
| Haiku 4.5 | $0.00002 | $0.00108 |
Grade A, and why
prompt-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 11d 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trace. On load, print first:
=============== [prompt-engineer/commands/prompt-review.md] [prompt-engineer] ===============
Prompt Review
Goal: Scan target prompts and report ground rule violations.
Input: $ARGUMENTS (file path, directory, or glob pattern)
Constraints:
- Do NOT modify any files
- Do NOT report issues without citing the violated rule number
Steps
- Read knowledge files:
../knowledge/actor-ground-rules.md,../knowledge/quality-checks.md,../knowledge/separation-of-concerns.md→ checklist loaded - Resolve target:
- File path → single file
- Directory → find all
.mdfiles with prompt frontmatter (hasname:ordescription:in YAML) - No target → ask: "(A) all agents, (B) all commands, (C) specific path"
- For each file, check:
a. Separation of concerns per knowledge/separation-of-concerns.md → boundary violations = HIGH
b. Actor ground rules 1 + 3 per knowledge/actor-ground-rules.md: Goal, Input, Steps, Output (rule 1) and Constraints (rule 3) sections exist → missing = HIGH
c. Role (rule 2): agents have Role, commands do not → violation = MEDIUM
d. Steps (rule 5): each step has observable result → vague steps = MEDIUM
e. Example Output (rule 10): section exists with synthetic example → missing = HIGH — unless the actor cites a leaner contract (
core/actor-template,lsa/CORE.md §4) per actor-ground-rules.md §Scope; then exempt (no finding) f. Output spec (rule 4): format and length defined → missing = MEDIUM g. Wording (rule 9): check for adverbs, hedging, filler, passive voice → each = LOW h. Assumptions (rule 7): check for unverified claims ("probably", "likely", "usually") → each = MEDIUM i. Apply KISS/DRY checks per knowledge/quality-checks.md → each = MEDIUM j. Apply AI Over-Engineering checks per knowledge/quality-checks.md → formalized common sense, reinvented paradigms, arbitrary thresholds = MEDIUM; example bloat, missing paradigm provenance = LOW k. Apply Context Budget checks per knowledge/quality-checks.md → restating/mergeable = MEDIUM, padding = LOW l. Show-changes-inline (author-time,core/outputRule 7) — WARNING-ONLY: in prompt SOURCE files (**/SKILL.md,**/agents/*.md), flag any step body that describes a write/edit/mark action (verbs: write/edit/append/replace/mark/update/create a file) WITHOUT an accompanying show-changes-inline directive (an instruction to quote the changed content inline, or afile:linecite ofcore/outputRule 7 / its Single-change template). This catches the omission in the prompt source before the skill ships (see../../core/skills/output/SKILL.md§"How this gets enforced"). Each hit = WARNING (signal, not gate), cited as<file>:<line>+ the write-verb + "no show-changes directive". Steps that only read, dispatch, or present (no artifact write) are exempt. m. Example Output consistency (rule 11): where an## Example Outputsection exists, the example matches the declared Output format and length → mismatch = MEDIUM - Compile all findings — re-derive contested judgment calls per
../knowledge/quality-checks.md§Severity Levels (self-consistency: drop findings that do not recur) → output table
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.
- 11d ago First seen · 59 lines · 22 tokens per session scan A 8d8a9e34420f
prompt-review is a command published in the GitHub repository NVZver/claude-marketplace (1 stars, last pushed 17d ago), licensed MIT. It adds 22 tokens to every session and 1,076 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 commands, from other repositories
prompt-generator
Generate effective prompts for Claude 4.5 Sonnet to achieve user-defined outcomes.
structured-output-doctor
Find LLM calls whose output is parsed as JSON and harden them with native structured output plus validate-and-retry.
token-cost-audit
Audit LLM call sites for token and cost waste, quantify the savings, and apply the safe wins.
p
Prompt optimizer · clarify only if needed, rewrite your request into a sharper prompt, then carry it out. Prefix --dry to stop at the rewrite.
fix-prompt
Fix and improve a rough prompt — show the cleaned version and the changes before acting on it.
prompt-history
Manage history of created and optimized prompts.