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 ai-analyst-lab/ai-analyst-plugin --skill context-comparegit clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-pluginWrote 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/ai-analyst-lab/ai-analyst-plugin/context-compare)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/context-compare"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/context-compare/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/ai-analyst-lab/ai-analyst-plugin/context-compare"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/context-compare.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 | $0.00072 | $0.01690 |
| Opus 5.5 | $0.00029 | $0.00676 |
| Sonnet 5.5 | $0.00014 | $0.00338 |
| Haiku 4.5 | $0.00007 | $0.00169 |
Grade A, and why
context-compare 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 2mo 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.
This is a copy
97% identical to context-compare — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Context compare (with and without)
Purpose
Measure what a piece of context is doing, instead of asserting it. Run the same question two ways, once without the context (for example, no metric definition) and once with it, and report the delta: did the spread collapse, did the runs start citing the definition, did the verdict go from drifts to stable. The setup whose presence collapses the drift is the context that moves the answer. Convergence is stability, not correctness.
Invocation
/context-compare "<the question>" --with <the definition> [N]
Default N = 5. The context under test is a meaning-only definition, usually a metric definition: the
user states it in conversation, points at a definition YAML file, or names an entry already in the
metric dictionary. The baseline is the analyst with that definition absent from the dictionary.
Example: /context-compare "What's our retention rate?" --with "Retention Rate (30d): share of accounts at least 30 days old that were active in the trailing 30 days"
How to run it
This skill is glue plus bookkeeping, and the whole procedure is manual: you stage the definition into the active dataset's metric dictionary, run the reliability procedure once per arm, compute the delta between the two arms, and restore the dictionary. The run step is the reliability skill (a sibling of this one); the per-arm statistics come from that skill's bundled script. The user never types a command; you do each step. This skill ships no scripts of its own.
Script path. The stats script is bundled with the reliability skill:
scripts/reliability_stats.py inside the reliability skill's directory, which sits next to this
one (from this skill's own directory the relative path is
../reliability/scripts/reliability_stats.py). If the skill install path cannot be resolved
(some sandboxed environments): read the script file from the reliability skill, write a copy into a
scripts/ folder inside the working folder, and run it from there. The script is self-contained.
In every case run it from the working-folder root, so its audit-log append lands in
.knowledge/reliability/log.jsonl.
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.
- 2mo ago First seen · 118 lines · 72 tokens per session scan A 7ee7127dbc3e
context-compare is a skill published in the GitHub repository ai-analyst-lab/ai-analyst-plugin (34 stars, last pushed 2mo ago), licensed MIT. It adds 72 tokens to every session and 1,690 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to context-compare, differing in 6 lines, and is treated as a copy.
context-compare compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| context-compareai-analyst-lab/ai-analyst-plugin | Skill | 34 | 2mo ago | MIT | A | 72 | Claude Code |
| agent-platform-model-registrygoogle/skills | Skill | 22k | yesterday | Apache-2.0 | A | 60 | Claude Code, Codex |
| foundry-config-setupmicrosoft/agent-framework | Skill | 15k | yesterday | MIT | A | 65 | Claude Code, Codex |
| google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skills | Skill | 22k | yesterday | Apache-2.0 | A | 132 | Claude Code, Codex |
| training-checkwanshuiyin/Auto-claude-code-research-in-sleep | Skill | 19k | 3d ago | MIT | A | 35 | Claude Code |
| nemo-automodel-launcher-configNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 30 | Claude Code |
| finetuningmicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 132 | Claude Code |