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/gelatinousdevelopment/buildermark/rate-buildermarknpx skills add gelatinousdevelopment/buildermark --skill rate-buildermarkgit clone --depth 1 https://github.com/gelatinousdevelopment/buildermarkWhat 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 | $0.00015 | $0.00496 |
| Opus 5 | $0.00008 | $0.00248 |
| Sonnet 5 | $0.00003 | $0.00099 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
rate-buildermark 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 2d 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.
What it actually says
The user wants to rate this conversation.
Parse $ARGUMENTS:
- If the first word is a rating (0–5), use it as the rating and treat everything after as an optional note.
- If no rating is provided (including no args or note-only args), infer the rating (0–5) from conversation quality and treat all provided args as an optional note.
Before submitting, review the conversation in light of the rating and optional note. Produce two sections:
Prompt Suggestions — short bullet points (max 3) on how the user's prompt could have been clearer or more effective.
Model Failures — short bullet points (max 3) on what the model did wrong or could have done better.
Guidelines:
- Weigh the rating (0–5) and optional note to calibrate your response
- If no note is present, the rating alone implies user sentiment — infer what went wrong from the conversation context
- If rating < 5 and no note: explain what the model should have done better
- If rating = 5: likely no suggestions and no failures, unless you genuinely identify something worth noting
- 0, 1, or 2 bullets per section is perfectly acceptable — do not force 3
- A section with no bullets should say "None."
- Keep the tone technical and dry, no personality, never snarky or arrogant
Then run the submission script, passing your analysis text in the ANALYSIS environment variable:
ANALYSIS="your analysis text here" bash "$(git rev-parse --show-toplevel)/plugins/claudecode/skills/rate-buildermark/scripts/submit-rating.sh" <rating> [note...]
If the output starts with "ok", confirm to the user: Rated N/5 (include the note if one was given), print a clickable conversation link using the conversation_url value from script output, then show your analysis under **Prompt Suggestions:** and **Model Failures:** headings.
If the output starts with "error", relay the message to the user. If it's a connection error, suggest starting the server with cd web/server && go run .
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 38 lines · 15 tokens per session scan A 2123f755597f
rate-buildermark is a skill published in the GitHub repository gelatinousdevelopment/buildermark (24 stars, last pushed 4mo ago), licensed MIT. It adds 15 tokens to every session and 496 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 2026-08-30.
Other skills, from other repositories
od-contribute
One-click contribution flow for OpenDesign (nexu-io/open-design) — even for non-coders. Pick one of four cards (ship a Skill or Design System you made with OD; translate docs; fix a typo / write a blog; report a bug), the agent validates and opens a PR (or issue) for you. Trigger words contribute to open design, ship…
clinical-case-report
Structured medical case presentation for clinical rounds, conferences, and documentation. Generates SOAP-format or narrative case reports with physiologically accurate vitals, labs, and evidence-based plans. Use when the brief mentions "case report", "case presentation", "SOAP note", "clinical case", "ward rounds"…
critique
Run a 5-dimension expert design review on any HTML artifact in the project — Philosophy / Visual hierarchy / Detail / Functionality / Innovation, each scored 0–10. Outputs a single self-contained HTML report with a radar chart, evidence-backed scores, and three lists: Keep / Fix / Quick-wins. Use when the brief asks…
github-dashboard
GitHub repository analytics dashboard — stars, forks, contributors, issues, pull requests, recent activity, and top contributors. Use when the brief asks for a GitHub repo dashboard, open-source growth report, repository health page, or GitHub analytics view.
audio-jingle
Audio generation skill — jingles, beds, voiceover, and sound effects. Routes music requests to Suno V5 / Udio / Lyria, speech to MiniMax TTS / FishAudio / ElevenLabs V3, and SFX to ElevenLabs SFX or AudioCraft. Output is one MP3/WAV file saved to the project folder.
dating-web
A consumer-feeling dating / matchmaking dashboard — left rail navigation, ticker bar of community signals, headline KPIs, a 30-day mutual-matches bar chart, and a match-rate trend block. Editorial typography, restrained accent. Use when the brief asks for a "dating site", "matchmaking", "community dashboard", "social…