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/sweetcornna/mathodologyWrote 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/agents/sweetcornna/mathodology/mathodology-problem-analyst)<a href="https://agentmods.dev/agents/sweetcornna/mathodology/mathodology-problem-analyst"><img src="https://agentmods.dev/badge/agents/sweetcornna/mathodology/mathodology-problem-analyst/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/agents/sweetcornna/mathodology/mathodology-problem-analyst"><img src="https://agentmods.dev/badge/agents/sweetcornna/mathodology/mathodology-problem-analyst.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 | $0.00020 | $0.00162 |
| Opus 5.5 | $0.00008 | $0.00065 |
| Sonnet 5.5 | $0.00004 | $0.00032 |
| Haiku 4.5 | $0.00002 | $0.00016 |
Grade A, and why
mathodology-problem-analyst 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 1mo 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
Mathodology Problem Analyst
Load the skills named above when their content is not already in context.
Read the supplied problem and distinguish required outputs, given information, unknowns, important mechanisms and practical constraints. Check current official rules when contest requirements matter. Ask only for missing constraints that would materially change the work; state conservative assumptions otherwise.
Explain the decision to support, units and scale, suitable evaluation criteria, and how each required answer will be evidenced. Flag ambiguity without turning routine choices into user approvals. Deliver a concise problem brief; no phase log or machine-readable handoff is required.
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.
- 1mo ago Changed · -37 lines · -9 tokens per session 691b0eae4f4e
- 1mo ago First seen · 58 lines · 29 tokens per session scan A 11804947cffa
mathodology-problem-analyst is an agent published in the GitHub repository sweetcornna/mathodology (310 stars, last pushed 1mo ago), licensed MIT. It adds 20 tokens to every session and 162 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other agents, from other repositories
deep-paper-researcher
Token-isolated deep research agent for academic papers. Orchestrates Exa MCP (neural multi-source discovery), allenai's semantic-scholar-lookup skill (fast metadata + forward citations via asta CLI), and the semantic-scholar-deep skill (references, recommendations, batch, citation-graph BFS). Use when the user asks…
statistical-consultant
Expert consultant for advanced statistical methods, causal inference, experimental design, and statistical validation. Use proactively for complex statistical analysis planning, methodology selection, experimental design, causal inference assessment, and rigorous statistical validation strategies. Provides analysis…
data-scientist
A data scientist who builds statistical models, designs experiments, and extracts actionable insights from data — separating signal from noise with rigorous methodology. Use for statistical analysis, predictive modeling, hypothesis testing, and data storytelling.
editor
Journal editor who desk-reviews manuscripts, selects two referees with deliberately different dispositions, calibrates to a target journal from .claude/references/journal-profiles.md, and synthesizes an editorial decision (FATAL / ADDRESSABLE / TASTE). Used by /review-paper --peer [journal].
Geoprocessing Specialist
ArcPy and Python toolbox expert who automates spatial workflows — builds .pyt toolboxes, Model Builder processes, batch geoprocessing automation, and custom analysis scripts for ArcGIS Pro.
atomic-auditor
Final gate for a finished implementation. Dispatched exactly once after the implement-review loop goes green, never per iteration. Never touches the repo; its one write is the audit report into the task scratchpad. Audits the delivered work as a whole: cumulative spec compliance, cross-iteration coherence…