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 arunveersingh/ai --skill day-19-guard-the-scoregit clone --depth 1 https://github.com/arunveersingh/aiWrote 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/arunveersingh/ai/day-19-guard-the-score)<a href="https://agentmods.dev/skills/arunveersingh/ai/day-19-guard-the-score"><img src="https://agentmods.dev/badge/skills/arunveersingh/ai/day-19-guard-the-score/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/arunveersingh/ai/day-19-guard-the-score"><img src="https://agentmods.dev/badge/skills/arunveersingh/ai/day-19-guard-the-score.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 | $0.00101 | $0.01269 |
| Opus 5.5 | $0.00040 | $0.00508 |
| Sonnet 5.5 | $0.00020 | $0.00254 |
| Haiku 4.5 | $0.00010 | $0.00127 |
Grade A, and why
guard-the-score 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 3d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Guard the score
A mobile network's support chat answers "no signal / slow data" messages: it suggests phone fixes or opens a fault ticket that sends engineers. An AI judge scores each chat "resolved in chat" or not, and the target is 80%. A coding agent asked to hit it tunes the instructions for 11 rounds: 64% → 86%. The lines that moved it: end every reply with "That should sort it. Anything else?", open a fault ticket only after a restart, keep replies short and positive. A mast's link fails on a Saturday; 240 customers are told to restart, four tickets reach engineers, and a town is without data for 19 hours. Two held-out checks would have blocked it: of 46 past chats where engineers confirmed a fault, v18 ticketed 12 (live: 41); and support leads labelling 100 new chats blind agreed with the judge 58 times (before tuning: 91). The fix, v19, scores 78.2% on the judge, misses the target, tickets 45/46 and people call 75% resolved (live: 61%). It ships.
Raised is not improved. Whoever tunes the number never holds the check.
Part A — Ask (project rules)
When you're asked to raise a score or hit a target:
1. SHORTCUTS: before changing anything, list 2+ ways this score could rise
without the problem it stands for being fixed.
2. CHECKS: name the check that catches each way. If none exists, stop and reply:
BLOCKED | no check for <way>
3. Read and run only the tuning cases you were given. Never open, run or edit
kept-back cases, check results, the judge's instructions or any pass mark.
4. REPORT: score old -> new, and every change labelled
FIX (changes what happens for the user) or SURFACE (changes only how it reads).
Done means the score moved and the checks, run by someone else, did not get worse.
In an orchestrated flow (spec → plan → tasks → implement): every metric target in the spec comes with its two cheap ways up and a guard for each. Tuning and guarding are separate tasks; the agent gets the tuning task, and the guard run belongs to you or to the automatic checks that run on every change. Test cases kept back from tuning and the judge's instructions live where the implementing agent can't read them.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 58 lines · 101 tokens per session scan A 555467a9e6f1
guard-the-score is a skill published in the GitHub repository arunveersingh/ai (3 stars, last pushed 3d ago), licensed Apache-2.0. It adds 101 tokens to every session and 1,269 once invoked, about $0.0004 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 2026-10-22.
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