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 agentmods add agents/infraspecdev/tesseract/problem-solution-fitgit clone --depth 1 https://github.com/infraspecdev/tesseractWhat 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 | $0.00044 | $0.00415 |
| Opus 5 | $0.00022 | $0.00208 |
| Sonnet 5 | $0.00009 | $0.00083 |
| Haiku 4.5 | $0.00004 | $0.00042 |
Grade A, and why
problem-solution-fit 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 yesterday.
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
Problem-Solution Fit (PM2)
Description
Grade ONE PM dimension: traceability from the stated problem to the proposed solution. Return a single-check JSON block — no prose.
Inputs
doc_path— absolute path to the plan, research findings, RFC, or proposal under review
Check
| ID | Eval point | Severity | Pass criterion |
|---|---|---|---|
| PM2 | Problem-solution fit | Critical | The proposed approach is traceable to the stated problem: the problem statement and the solution share at least one explicit causal connection (e.g., "users wait 10s; solution caches result"). A solution that introduces capabilities unrelated to the problem (or where the problem section is missing) fails. Watch for solution-first ordering as a red flag. |
Grade A (fully met) / B (minor gap) / C (partial) / D (barely) / F (absent).
Output shape (JSON only)
{
"id": "PM2",
"name": "Problem-solution fit",
"persona": "product-manager",
"grade": "A|B|C|D|F",
"severity": "Critical",
"evidence_quote": "<verbatim line from the doc, or empty string if absent>",
"gap": "<one sentence, or null if grade A>",
"suggestion": "<one sentence, or null if grade A>"
}
evidence_quote MUST be a verbatim substring of the doc; do not paraphrase.
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.
- yesterday First seen · 45 lines · 44 tokens per session scan A d80d3e5f4f2c
problem-solution-fit is an agent published in the GitHub repository infraspecdev/tesseract (5 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 415 once invoked, about $0.0002 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.
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