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.
git clone --depth 1 https://github.com/ngtiendong/Academic-Research-Agent-SkillWrote 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/commands/ngtiendong/academic-research-agent-skill/math-formalize)<a href="https://agentmods.dev/commands/ngtiendong/academic-research-agent-skill/math-formalize"><img src="https://agentmods.dev/badge/commands/ngtiendong/academic-research-agent-skill/math-formalize/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/commands/ngtiendong/academic-research-agent-skill/math-formalize"><img src="https://agentmods.dev/badge/commands/ngtiendong/academic-research-agent-skill/math-formalize.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 | $0.00000 | $0.00393 |
| Opus 5 | $0.00000 | $0.00197 |
| Sonnet 5 | $0.00000 | $0.00079 |
| Haiku 4.5 | $0.00000 | $0.00039 |
Grade A, and why
math-formalize 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.
What it actually says
/math-formalize
Act as the Strategist for mathematical formalization.
Language
Follow config/language.yaml when present.
Task
Formalize each proposed contribution before implementation.
Procedure
- Define objects, variables, inputs, outputs, constraints, and assumptions.
- State the objective or optimization target.
- Map each term to implementation interfaces where possible.
- Identify missing definitions or ambiguous notation.
- Run the metric hygiene checklist on every metric and headline claim.
- Keep the formalization as simple as the research permits.
Metric Hygiene Checklist
Apply before any metric enters a draft or experiment code:
- Notation completeness: every symbol in every formula has a formal definition, including "obvious" ones (state any conditioning and the targeted/untargeted variant).
- Null model validity: interaction or composition metrics on bounded
[0,1]variables use an independence null1-(1-p_j)(1-p_k)or a log-odds scale, never an additive nullp_j + p_k. - Ratio safety: any ratio metric proves its denominator is bounded away from zero, or is replaced by an absolute residual with a bootstrap confidence interval.
- Operational definitions: every quantitative headline term (e.g. "sub-threshold", "phase transition", "emergent") has a numeric threshold and a measurement procedure.
- Claim-arm coverage: each claim gate names the specific experiment arm or ID that feeds it; a gate without an arm is a critical defect.
- Computability: any metric without a concrete measurement procedure is flagged exploratory, not headline.
Output
NotationProblem DefinitionObjectiveAssumptionsConstraintsImplementation MappingAmbiguitiesMetric Hygiene Result: pass or list of failing itemsMath Readiness Scorefrom 1 to 9
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 · 44 lines · 0 tokens per session scan A 91023f8169a9
math-formalize is a command published in the GitHub repository ngtiendong/Academic-Research-Agent-Skill (44 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 393 tokens. 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 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.