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 flonat/flonat-research --skill symbolic-checkgit clone --depth 1 https://github.com/flonat/flonat-researchWrote 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/flonat/flonat-research/symbolic-check)<a href="https://agentmods.dev/skills/flonat/flonat-research/symbolic-check"><img src="https://agentmods.dev/badge/skills/flonat/flonat-research/symbolic-check/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/flonat/flonat-research/symbolic-check"><img src="https://agentmods.dev/badge/skills/flonat/flonat-research/symbolic-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00061 | $0.01942 |
| Opus 5 | $0.00030 | $0.00971 |
| Sonnet 5 | $0.00012 | $0.00388 |
| Haiku 4.5 | $0.00006 | $0.00194 |
Grade A, and why
symbolic-check 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 7d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Symbolic Check: Prove/Refute a Self-Authored Algebra Step with a CAS
Verify a symbolic manipulation you wrote — an identity, a derivative, a limit, a comparative-static sign, a closed form — using sympy. Unlike numerical falsification, this can positively verify the step: a CAS-confirmed identity is correct.
When to Use
- You wrote
A = B,∂f/∂x = g,lim = L,sign(∂f/∂x) = −, or "the closed form is …" and want it proven before it ships. symbolic-check, "verify this algebra / derivative / limit", "check the comparative-static sign", "does this closed form equal the original".- Companion to
mark-unverifiedfor self-authored algebra (the derivative-sign / closed-form family the rule explicitly names).
When NOT to Use
| Situation | Use instead |
|---|---|
| A full theorem/lemma you want machine-proven end-to-end | lean-check (R3) |
| A distributional / probabilistic claim over a parameter space | numerical-check (R1) |
| Re-verify a computed empirical result | cross-language-check |
| Conceptual / assumption review | domain-reviewer |
Position in the verification spectrum
R2 — symbolic / CAS. Can VERIFY (prove) or FALSIFY a symbolic step; between numerical falsification (R1) and formal proof (R3) in strength. It proves algebra, not arbitrary theorems — reasoning beyond symbolic manipulation (measure theory, limits sympy can't evaluate) escalates to lean-check or domain-reviewer.
Procedure
1. Transcribe the claim precisely, with declared symbol domains
- Restate the exact claim: identity
A == B, derivativediff(f,x) == g, limitlimit(f,x,a) == L, signsign(diff(f,x))over a domain, or closed formexpr == cf. - Declare assumptions on the symbols —
symbols('x', positive=True, real=True)etc. Comparative-static signs and simplifications are wrong without the right domain. State them explicitly (they are part of the claim).
2. Prove the core with .equals(), not simplify(...)==0
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.
- 7d ago First seen · 117 lines · 61 tokens per session scan A ca47c80ba380
symbolic-check is a skill published in the GitHub repository flonat/flonat-research (133 stars, last pushed 16d ago), licensed MIT. It adds 61 tokens to every session and 1,942 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 2026-09-03.
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