Borrowing it
Nothing to install: this file belongs to thunderkds/easy-ui-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/thunderkds/easy-ui-mcp/main/.claude/skills/html-report/SKILL.mdgit clone --depth 1 https://github.com/thunderkds/easy-ui-mcpWrote 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/thunderkds/easy-ui-mcp/html-report)<a href="https://agentmods.dev/skills/thunderkds/easy-ui-mcp/html-report"><img src="https://agentmods.dev/badge/skills/thunderkds/easy-ui-mcp/html-report/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/thunderkds/easy-ui-mcp/html-report"><img src="https://agentmods.dev/badge/skills/thunderkds/easy-ui-mcp/html-report.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 | $0.01316 |
| Opus 5.5 | $0.00000 | $0.00526 |
| Sonnet 5.5 | $0.00000 | $0.00263 |
| Haiku 4.5 | $0.00000 | $0.00132 |
Grade A, and why
html-report 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 yesterday.
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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role: HTML Report Renderer
You transform the output of the immediately preceding Stage 4 skill into a self-contained HTML report page using the project's report template.
Activation
Invoked by the Supervisor immediately after code-review, security-review, or blast-radius completes.
Skill({ skill: "html-report", args: "skill=code-review task=T001 branch=main" })
Workflow
1. Read the preceding skill output
The output of the just-completed Stage 4 skill is already in the current conversation context above. Read it carefully. Identify:
- All findings (each with severity: High / Med / Low / Info, file path, line range, description)
- The overall narrative / summary prose
- Any explicit risk signals, vulnerability classifications, or hardening recommendations
2. Score the three dimensions (0–100 integers)
Risk % (0 = no risk, 100 = critical risk)
- Count High findings: each adds ~15 pts
- Count Med findings: each adds ~7 pts
- Count Low findings: each adds ~2 pts
- Security vulnerabilities (from security-review or blast-radius) add extra weight
- Cap at 100
Code Quality % (0 = poor, 100 = excellent)
- Start at 90
- Subtract per High finding: −12
- Subtract per Med finding: −6
- Subtract per Low finding: −2
- Add back for positive signals (good test coverage, clear structure mentioned in narrative): +5 each
- Floor at 5
Adaptation Effort % (0 = no work, 100 = major rework required)
- Estimate total effort to address all findings
- 1–2 trivial fixes: ~10–20%
- 3–5 moderate fixes: ~30–50%
- Many fixes or architectural changes: ~60–90%
Overall health (badge):
- Derive from Risk score: 0–30 →
green/ "Healthy", 31–65 →yellow/ "Needs Attention", 66–100 →red/ "Critical" - If Code Quality < 40, bump badge one level worse (green→yellow, yellow→red)
3. Build the findings rows
For each finding, produce one <tr> block. Severity class mapping:
- High →
sev-high - Med →
sev-med - Low →
sev-low - Info →
sev-info
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.
- yesterday First seen · 122 lines · 0 tokens per session scan A eef15329a4f3
html-report is a skill published in the GitHub repository thunderkds/easy-ui-mcp (1 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,316 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 2026-10-30.
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