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 OpenLAIR/OpenSkill --skill evo-citation-scorergit clone --depth 1 https://github.com/OpenLAIR/OpenSkillWrote 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/openlair/openskill/evo-citation-scorer)<a href="https://agentmods.dev/skills/openlair/openskill/evo-citation-scorer"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-citation-scorer/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/openlair/openskill/evo-citation-scorer"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-citation-scorer.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 | $0.00042 | $0.00310 |
| Opus 5 | $0.00021 | $0.00155 |
| Sonnet 5 | $0.00008 | $0.00062 |
| Haiku 4.5 | $0.00004 | $0.00031 |
Grade A, and why
evo-citation-scorer 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 today.
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
evo-citation-scorer
Scores and classifies citations as real or fake.
Key Functions
normalize_string(text)- Normalize for comparison (lowercase, no punctuation)calculate_title_similarity(title1, title2)- Token-based title similarity (0-100)compute_composite_score(citation, api_result)- Multi-factor score (title 50%, author 30%, year 20%)classify_citation(verification_result)- Classify as Real/Fake based on scoresexport_fake_citations_json(fake_titles, output_file)- Write sorted JSON output
Classification Logic
- DOI resolves via CrossRef → Real
- No DOI or DOI fails → search CrossRef by title
- Best composite score >= 70 → Real
- Below 70 → Fake
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-citation-scorer/scripts')
from utils import classify_citation, export_fake_citations_json
# After verification
status = classify_citation(verification_result)
if status == 'Fake':
fake_titles.append(verification_result['title'])
export_fake_citations_json(fake_titles, '/root/answer.json')
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.
- today First seen · 39 lines · 42 tokens per session scan A d1d2db633360
evo-citation-scorer is a skill published in the GitHub repository OpenLAIR/OpenSkill (88 stars, last pushed yesterday), licensed Apache-2.0. It adds 42 tokens to every session and 310 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 2026-09-11.
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