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 hidai25/eval-view --skill watchgit clone --depth 1 https://github.com/hidai25/eval-viewWrote 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/hidai25/eval-view/watch)<a href="https://agentmods.dev/skills/hidai25/eval-view/watch"><img src="https://agentmods.dev/badge/skills/hidai25/eval-view/watch/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/hidai25/eval-view/watch"><img src="https://agentmods.dev/badge/skills/hidai25/eval-view/watch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00018 | $0.00555 |
| Opus 5.5 | $0.00007 | $0.00222 |
| Sonnet 5.5 | $0.00004 | $0.00111 |
| Haiku 4.5 | $0.00002 | $0.00056 |
Grade A, and why
watch 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Watch Mode
Use this skill when the user wants continuous regression monitoring during development. Watch mode observes file changes and automatically re-runs evalview check with debounced triggers.
What this does
EvalView's watch mode uses watchdog to monitor directories for file changes (.py, .yaml, .yml, .json, .md, .txt, .toml, .cfg, .ini). When a change is detected, it runs a regression check via the gate() API and displays a live scorecard with pass/fail status, score deltas, tool changes, and streak tracking.
How to start watch mode
Watch mode is a CLI command (not an MCP tool). Help the user run it:
evalview watch
Common options
--quick— Skip LLM judge, deterministic checks only ($0 cost, sub-second)--path src/ --path tests/— Watch specific directories (default: current directory)--test "my-test"— Only check a specific test by name--test-dir tests/evalview— Path to test cases directory (default:tests)--interval 1— Debounce interval in seconds (default: 2.0)--fail-on REGRESSION,TOOLS_CHANGED— Comma-separated statuses that count as failure (default: REGRESSION)--sound— Terminal bell on regression
Examples
# Basic: watch everything, full checks
evalview watch
# Fast development loop: no LLM judge, 1-second debounce
evalview watch --quick --interval 1
# Watch specific directories and one test
evalview watch --path src/ --path tests/ --test "calculator-division"
# Strict mode: fail on any behavioral change
evalview watch --fail-on REGRESSION,TOOLS_CHANGED,OUTPUT_CHANGED --sound
Prerequisites
Watch mode requires the watchdog package. If not installed:
pip install evalview[watch]
Notes
- Watch mode excludes
.evalview/,.git/,venv/,node_modules/,__pycache__/, and other common non-source directories automatically. - The initial check runs immediately on startup before watching begins.
- Results include a live scorecard with pass counts, regression counts, health percentage, and streak info.
--quickmode is ideal for tight development loops since it costs nothing and runs in sub-second time.
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 · 62 lines · 18 tokens per session scan A e7a3f0f50ff5
watch is a skill published in the GitHub repository hidai25/eval-view (140 stars, last pushed 5d ago), licensed Apache-2.0. It adds 18 tokens to every session and 555 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.
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