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-sec13f-analyzergit 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-sec13f-analyzer)<a href="https://agentmods.dev/skills/openlair/openskill/evo-sec13f-analyzer"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-sec13f-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/openlair/openskill/evo-sec13f-analyzer"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-sec13f-analyzer.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 | $0.00110 | $0.01013 |
| Opus 5 | $0.00055 | $0.00507 |
| Sonnet 5 | $0.00022 | $0.00203 |
| Haiku 4.5 | $0.00011 | $0.00101 |
Grade A, and why
evo-sec13f-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 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.
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.
evo-sec13f-analyzer
Utilities for SEC Form 13F-HR quarterly TSV analytics.
Key facts
- SEC EDGAR Release 22.4.1 (Jan 3, 2023): VALUE column is in exact dollars (multiplier = 1) for all filings from 2023 onward. Use
value_multiplier=1for the 2025-q2 / 2025-q3 data in this task. - CUSIP is a 9-char alphanumeric. Always load as string and zero-pad to length 9 to preserve leading zeros (Apple =
037833100). - TSV columns: tab-delimited, UTF-8.
PUTCALLblank = equity;PUT/CALL= options. Exclude options when counting equity positions.- AUM (gross portfolio value) lives in
SUMMARYPAGE.TABLEVALUETOTAL. Number of equity positions (unique CUSIPs) is computed from INFOTABLE. - Fund manager names vary in casing/punctuation. Use RapidFuzz
process.extractwithfuzz.WRatioandutils.default_processfor entity resolution againstCOVERPAGE.FILINGMANAGER_NAME.
Importing
import sys
sys.path.insert(0, '/app/environment/skills/evo-sec13f-analyzer/scripts')
from utils import (
load_coverpage, load_infotable, load_summarypage,
fuzzy_find_manager, get_fund_aum, get_fund_holdings,
compare_holdings, top_holders_of_cusip, find_cusip_for_issuer,
)
Typical workflow
cp_q3 = load_coverpage('/root/2025-q3/COVERPAGE.tsv')
it_q3 = load_infotable('/root/2025-q3/INFOTABLE.tsv')
sp_q3 = load_summarypage('/root/2025-q3/SUMMARYPAGE.tsv')
# Q1: fund AUM via fuzzy match
matches = fuzzy_find_manager(cp_q3, 'renaissance technologies', top_n=5)
accn = matches.iloc[0]['ACCESSION_NUMBER']
aum = get_fund_aum(sp_q3, accn)
# Q2: number of stocks held
holdings = get_fund_holdings(it_q3, accn)
n_stocks = len(holdings)
# Q3: top buys delta
holdings_q2 = get_fund_holdings(it_q2, accn_q2)
holdings_q3 = get_fund_holdings(it_q3, accn_q3)
deltas = compare_holdings(holdings_q2, holdings_q3)
top_buys_cusips = deltas.head(5)['CUSIP'].tolist()
# Q4: top holders of a CUSIP
plt_cusip = '69608A108' # Palantir Class A
top3 = top_holders_of_cusip(it_q3, cp_q3, plt_cusip, n=3)
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 · 67 lines · 110 tokens per session scan A 287312601877
evo-sec13f-analyzer is a skill published in the GitHub repository OpenLAIR/OpenSkill (88 stars, last pushed yesterday), licensed Apache-2.0. It adds 110 tokens to every session and 1,013 once invoked, about $0.0006 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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