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 JeffBrines/openfpa --skill fpa-capture-correctiongit clone --depth 1 https://github.com/JeffBrines/openfpaWrote 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/jeffbrines/openfpa/fpa-capture-correction)<a href="https://agentmods.dev/skills/jeffbrines/openfpa/fpa-capture-correction"><img src="https://agentmods.dev/badge/skills/jeffbrines/openfpa/fpa-capture-correction/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/jeffbrines/openfpa/fpa-capture-correction"><img src="https://agentmods.dev/badge/skills/jeffbrines/openfpa/fpa-capture-correction.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 | $0.00062 | $0.00894 |
| Opus 5 | $0.00031 | $0.00447 |
| Sonnet 5 | $0.00012 | $0.00179 |
| Haiku 4.5 | $0.00006 | $0.00089 |
Grade A, and why
fpa-capture-correction 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.
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Capture a Correction (Operate)
Overview
A human reviewing a forecast is the highest-signal feedback there is - they catch
structural errors and domain knowledge the backtest can't see, and catch them now.
This skill turns that into durable memory: a typed correction in .fpa/corrections/
that grounds every future forecast.
Core principle: the human is the authority; capture, confirm interpretation once, then it persists. Everything is plain markdown the user owns.
The three correction types
- parametric - a concrete driver fix ("December runs ~2× a normal month"). Becomes
an
override(a config path + value) applied to every future forecast viapyfpa.apply_corrections. - structural - a methodology fix ("you're double-counting deferred revenue"). A pre-ratified structural proposal (the human authored it) - route it to fpa-learn-business to generate the skill/model change; do NOT wait for backtest misses.
- context - a one-time-item note ("that Q3 spike was a one-off contract"). Annotates so fpa-cfo-judgment's one-time screen keeps the backtest from "learning" a one-off.
Workflow
- Classify the correction (parametric / structural / context).
- Identify the target - the driver path (e.g.
channels[*].seasonality[11],working_capital.dio_days), line, or profile area. For parametric, draft the concreteoverride: {path, value}. - Write the correction with
pyfpa.save_correction. Setslugto a<date>-<short-name>string (e.g.2026-06-08-december-seasonality) -save_correctionuses the whole slug as the filename (.fpa/corrections/<slug>.md), so keep the date in it. Include frontmatter (type,target,status,date,override) and a markdown body (**Was off:** … **Correction:** … **Why:** [[…]]), linking to the assumption/profile it corrects with[[wikilinks]]. - Confirm interpretation. Echo back the concrete change ("I'll set December
seasonality to 2.0 on all channels - right?"). Only on confirmation set
status: applied. - Keep
.fpa/MEMORY.mdcurrent - the vault index (see below).
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 · 70 lines · 62 tokens per session scan A 2f3b01075e9f
fpa-capture-correction is a skill published in the GitHub repository JeffBrines/openfpa (6 stars, last pushed 2mo ago), licensed MIT. It adds 62 tokens to every session and 894 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 2026-08-31.
Other skills, from other repositories
comptable
Comptabilité, fiscalité et facturation pour entreprises françaises. Gère écritures PCG, déclarations TVA, IS/IR, clôture annuelle, liasse fiscale (2033/2065), FEC, états financiers, et chaîne facturation (mentions obligatoires, numérotation, Factur-X/UBL/CII, plateformes agréées PDP/PA, e-reporting, réforme 2026…
fiscaliste
Fiscaliste IA pour la fiscalité personnelle des particuliers français : optimisation et déclaration de l'impôt sur le revenu, IFI, revenus du capital, revenus fonciers, equity salarial, crypto-actifs et PER. Couvre le calcul de l'IR (barème, quotient familial, décote, PAS, CEHR, revenus exceptionnels), la déclaration…
syndic
Gère un parc de copropriétés en France avec vue portfolio consolidée. Couvre administration, comptabilité (décret 2005, plan comptable copro, 5 annexes), assemblées générales (convocation, PV, notification), appels de fonds, travaux, fournisseurs, recouvrement d'impayés et transition de syndic. Maîtrise les majorités…
financial-statement-analysis
Reads a set of financial statements and establishes what changed and why — fluctuation analysis against prior period and against budget, profitability, liquidity, solvency and efficiency ratios, benchmarking, and the non-GAAP measures presented alongside them. Use this to interpret results, review a counterparty's or…
ib-collar
Generate tactical collar strategy reports for protecting PMCC positions through earnings or high-risk events. Requires TWS or IB Gateway running locally.
ib-report-delta-adjusted-notional-exposure
Report delta-adjusted notional exposure across all IBKR accounts. Calculates option deltas using Black-Scholes and reports long/short exposure by account and underlying. Use when user asks about delta exposure, portfolio risk, or directional exposure.