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 Zhang-Henry/CoEvoSkills --skill evo-github-repo-analyticsgit clone --depth 1 https://github.com/Zhang-Henry/CoEvoSkillsWrote 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/zhang-henry/coevoskills/evo-github-repo-analytics)<a href="https://agentmods.dev/skills/zhang-henry/coevoskills/evo-github-repo-analytics"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-github-repo-analytics/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/zhang-henry/coevoskills/evo-github-repo-analytics"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-github-repo-analytics.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 | $0.00070 | $0.00620 |
| Opus 5 | $0.00035 | $0.00310 |
| Sonnet 5 | $0.00014 | $0.00124 |
| Haiku 4.5 | $0.00007 | $0.00062 |
Grade A, and why
evo-github-repo-analytics 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 10d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Repository Analytics Skill
This skill fetches PR and issue data from the GitHub Search API and produces a structured JSON report with PR counts, merge statistics, top contributors, bug report counts, and resolved bug counts.
Key Concepts
- Cohort selection: PRs/issues are selected by
createddate range - PR states:
merged(has merged_at) vsclosed(state=closed, no merged_at) are tracked separately - Merge duration:
mergedAt - createdAtin days, averaged and rounded to 1 decimal - Bug detection: Any issue with at least one label containing substring 'bug' (case-insensitive)
- Resolved bugs: Bug issues whose
closed_atfalls within the specified period - Pagination: Handles multi-page results (100 per page)
- Top contributor: By PR count, alphabetical tie-break
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-github-repo-analytics/scripts')
from utils import generate_report, validate_report
# Generate the report
report = generate_report(
repo='cli/cli',
start_date='2024-12-01',
end_date='2024-12-31',
output_path='/app/report.json'
)
# Validate the output
validate_report('/app/report.json')
Output Format
{
"pr": {
"total": "<int> PRs created in period",
"merged": "<int> PRs merged (as of now)",
"closed": "<int> PRs closed without merge (as of now)",
"avg_merge_days": "<float> average days from creation to merge, 1 decimal",
"top_contributor": "<str> GitHub login with most PRs created"
},
"issue": {
"total": "<int> issues created in period",
"bug": "<int> issues with a label containing 'bug'",
"resolved_bugs": "<int> bug issues closed during the period"
}
}
Functions
fetch_all_search_results(repo, item_type, created_range)- Paginated GitHub searchanalyze_prs(items)- Compute PR statistics from search resultsanalyze_issues(items, month_start, month_end)- Compute issue statisticsgenerate_report(repo, start_date, end_date, output_path)- End-to-end entry pointvalidate_report(report_path)- Validate output JSON structure and types
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.
- 10d ago First seen · 67 lines · 70 tokens per session scan A 7601f9341033
evo-github-repo-analytics is a skill published in the GitHub repository Zhang-Henry/CoEvoSkills (66 stars, last pushed 20d ago), licensed Apache-2.0. It adds 70 tokens to every session and 620 once invoked, about $0.0003 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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