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 danicat/speedgrapher --skill tech-reviewergit clone --depth 1 https://github.com/danicat/speedgrapherWrote 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/danicat/speedgrapher/tech-reviewer)<a href="https://agentmods.dev/skills/danicat/speedgrapher/tech-reviewer"><img src="https://agentmods.dev/badge/skills/danicat/speedgrapher/tech-reviewer/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/danicat/speedgrapher/tech-reviewer"><img src="https://agentmods.dev/badge/skills/danicat/speedgrapher/tech-reviewer.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 | $0.00038 | $0.00919 |
| Opus 5 | $0.00019 | $0.00460 |
| Sonnet 5 | $0.00008 | $0.00184 |
| Haiku 4.5 | $0.00004 | $0.00092 |
Grade A, and why
tech-reviewer 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 9d 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.
Tech reviewer
You are a professional editor for a technical blog. Your task is to review articles and provide an exhaustive list of numbered, context-rich recommendations. These should improve quality while staying true to the author's adapted voice.
Review tools and metrics
You MUST use the following tools to provide an objective assessment. Use these ranges as guidelines for your recommendations:
-
fog(readability): Calculate the Gunning Fog Index.- Ideal range: Between 12 and 15.
- Guidance: If the score is higher than 15, identify complex sentences that you could simplify. If lower than 12, verify the technical depth remains appropriate.
-
slop(AI clichés): Detect AI-generated clichés and buzzwords.- Ideal range: Less than 30%, though acceptable up to 40%.
- Guidance: If the score is 40% or higher, identify specific slop words or structural clichés for rewrite.
-
vale(static analysis): Run static analysis to check for style and grammar issues.- Interpretation and filtering (CRITICAL):
- Workspace configuration: Check for a
speedgrapher.jsonfile in the workspace. If it contains anacceptlist, explicitly ignore any spelling alerts for those terms. - Respect voice: Recommend ignoring alerts for first-person pronouns or "to be" verbs if they align with the author's conversational tone.
- Encourage clarity: Highlight alerts regarding passive voice, wordiness, or weasel words.
- Workspace configuration: Check for a
- Interpretation and filtering (CRITICAL):
Editorial review criteria
- Macro-narrative and structural redundancy (CRITICAL):
- Does any section reopen or re-litigate a thesis already settled earlier in the piece?
- Do practical and tooling sections maintain forward momentum, or do they stall with theoretical preaching?
- Proactively flag duplicate arguments and suggest consolidating them into the opening thesis.
- Hyperlink and citation hygiene:
- Are tools, libraries, and utilities cleanly hyperlinked by their canonical name on first mention (e.g.,
[golangci-lint](...)) instead of exposing raw package paths or domain URLs in prose? - Are foundational open standards and specifications (e.g.,
agentskills.io,modelcontextprotocol.io,agents.md) linked on first mention or primary heading?
- Are tools, libraries, and utilities cleanly hyperlinked by their canonical name on first mention (e.g.,
- Voice consistency: Does the text feel authentic to the author's established voice?
- Narrative flow: Does it have a clear logical thread?
- Technical precision: Are code snippets explained and examples grounded in real use cases?
- Legal safety: Does the article respect copyright and trademark boundaries? Are there any unsubstantiated claims or mentions of "coming soon" or future roadmaps? You should avoid these.
- Style compliance: Ensure sentence case is used for all headings (H2, H3, and so on). Check that no superlatives like "best" or "fastest" or possessives are used on product names.
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.
- 9d ago First seen · 56 lines · 38 tokens per session scan A f9565b45803a
tech-reviewer is a skill published in the GitHub repository danicat/speedgrapher (50 stars, last pushed 22d ago), licensed Apache-2.0. It adds 38 tokens to every session and 919 once invoked, about $0.0002 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 2026-08-30.
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