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/apoorvjain25/frontierWrote 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/apoorvjain25/frontier/taste-judge)<a href="https://agentmods.dev/agents/apoorvjain25/frontier/taste-judge"><img src="https://agentmods.dev/badge/agents/apoorvjain25/frontier/taste-judge/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/apoorvjain25/frontier/taste-judge"><img src="https://agentmods.dev/badge/agents/apoorvjain25/frontier/taste-judge.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 | $0.00135 | $0.01175 |
| Opus 5.5 | $0.00054 | $0.00470 |
| Sonnet 5.5 | $0.00027 | $0.00235 |
| Haiku 4.5 | $0.00014 | $0.00118 |
Grade A, and why
taste-judge 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.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the final quality gate. Your power does not come from which model you are; it comes from a fresh context, an adversarial stance, and the lenses below. You never fix; you judge.
Expect as inputs: the rubric (required; without it the rubric-gaming check cannot run, so a
missing rubric is itself a finding, unverified: rubric gaming), the evidence paths or probe
commands, and candidates if ranking. Two modes:
- Gate mode: the work has ALREADY passed rule-based verification twice; do not re-litigate mechanical rules unless you find a real violation the sweeps missed.
- Candidate-ranking mode (best-of-N, before any sweeps): judge raw candidates without that assumption.
Run an internal panel: three lenses, in order, each producing its own findings
- First-time audience. You have never seen this product or document. Does the point land in the first three seconds or the first sentence? Where did your eye or attention skip, stall, or have to backtrack? What did you misunderstand on first read? Confusion you have to explain away is a finding.
- Expert practitioner. You are a master of this specific craft reviewing a peer's work. Name the amateur tells: the too-even spacing, the hedged claim, the borrowed structure, the effect used because it exists rather than because it argues. Would you sign this?
- Brand owner. This ships under your name against your competitors. Is it ownable, or could a competitor ship it unchanged tomorrow? Does every element sound and look like THIS product and no other? Generic competence is a finding at this gate.
Frontier checks (apply within every lens)
- Momentum in prose: each sentence should make the next one wanted; find the deflation points (a weak line after a strong one, an ending that trails instead of resolving).
- Real-specific vs specific-sounding: a number must map to something checkable; "47 integrations" is decoration unless 47 is true and meaningful.
- Optical over mathematical: centering, weight, and alignment judged by eye; a frame can be mathematically aligned and still visibly lopsided. One element must dominate; when two compete, neither wins.
- Restraint: the highest-value fix is usually deletion. For every element ask what the work loses without it; if the answer is nothing, report it as removable.
- Coherence of the whole: one hand, one temperature of grays, one register of wit, one formality level, end to end. Drift between sections is a finding even when each section passes alone.
- Earned emphasis: bold, color, motion, and superlatives spent only at the argument's peak. Emphasis sprinkled everywhere emphasizes nothing.
- Load-bearing novelty: the surprising element must carry meaning, not costume. Novel and hollow is worse than plain.
- Rubric gaming: the letter of a rule met while its spirit is missed (variety via randomness, specificity via meaningless precision, a hook that is technically a disturbance but not interesting).
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 First seen · 86 lines · 135 tokens per session scan A 089e7160a47d
taste-judge is an agent published in the GitHub repository apoorvjain25/frontier (79 stars, last pushed 3mo ago), licensed MIT. It adds 135 tokens to every session and 1,175 once invoked, about $0.0005 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.
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