SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.
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 benchflow-ai/skillsbench --skill 13f-analyzergit clone --depth 1 https://github.com/benchflow-ai/skillsbenchWrote 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/benchflow-ai/skillsbench/13f-analyzer)<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/13f-analyzer"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/13f-analyzer/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/benchflow-ai/skillsbench/13f-analyzer"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/13f-analyzer.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 | $0.00323 |
| Opus 5 | $0.00019 | $0.00161 |
| Sonnet 5 | $0.00008 | $0.00065 |
| Haiku 4.5 | $0.00004 | $0.00032 |
Grade A, and why
13f-analyzer 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- 13f-analyzer — 100% identical, 0 lines differ
What it actually says
Overview
Analyze the holding summary of a particular fund in one quarter:
python3 scripts/one_fund_analysis.py \
--accession_number ... \
--quarter 2025-q2 \
This script will print out several basic information of a given fund on 2025-q2, including total number of holdings, AUM, total number of stock holdings, etc.
Analyze the change of holdings of a particular fund in between two quarters:
python scripts/one_fund_analysis.py \
--quarter 2025-q3 \
--accession_number <accession number assigned in q3> \
--baseline_quarter 2025-q2 \
--baseline_accession_number <accession number assigned in q2>
This script will print out the dynamic changes of holdings from 2025-q2 to 2025-q3. Such as newly purchased stocks ranked by notional value, and newly sold stocks ranked by notional value.
Analyze which funds hold a stock to the most extent
python scripts/holding_analysis.py \
--cusip <stock cusip> \
--quarter 2025-q3 \
--topk 10
This script will print out the top 10 hedge funds who hold a particular stock with highest notional value.
What ships with it
2 files 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.
- 9d ago First seen · 42 lines · 38 tokens per session scan A fac0b5f05405
13f-analyzer is a skill published in the GitHub repository benchflow-ai/skillsbench (1,764 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 323 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 2026-09-03.
Other skills, from other repositories
portfolio
Cross-chain DeFi portfolio discovery, rebalancing suggestions, and NEAR Intent construction. Activates when the user pastes a wallet address or asks about yield/positions/rebalancing. Bootstraps a per-user "portfolio" project, aggregates positions across all the user's addresses inside one project, and offers a…
trader-setup
One-time onboarding for the financial trader workflow — real-time alerts, position-aware relevance, decision journaling with outcome tracking. After successful setup this skill is excluded from selection until the marker file is deleted.
portfolio-analysis
Analyzing fund portfolios including AUM extraction, holdings counts, and portfolio composition.
fuzzy-fund-search
Fuzzy matching techniques for finding hedge funds by name when exact names are unknown.
sec13f-data-format
Understanding SEC 13-F filing data structure, TSV format, and key tables for hedge fund analysis.
13f-data-analysis
Analyze SEC 13-F filings data including AUM, holdings count, and cross-quarter comparisons using TSV files.