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-plus --skill comparegit clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-plusWrote 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-plus/compare)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plus/compare"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plus/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-plus/compare"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plus/compare.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 | $0.00115 | $0.01001 |
| Opus 5.5 | $0.00046 | $0.00400 |
| Sonnet 5.5 | $0.00023 | $0.00200 |
| Haiku 4.5 | $0.00012 | $0.00100 |
Grade A, and why
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 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: 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
/compare "<the question>" --with <setup_dir> [N]
Default N = 5. The setup is a directory of meaning-only definition overlays (for example the retention
definition at .knowledge/comparisons/conditions/c1_retention_contract/). The baseline is the analyst
with that setup absent.
Example: /compare "What's our retention rate?" --with .knowledge/comparisons/conditions/c1_retention_contract
How to run it
The math and the report live in the standalone eval tool (~/projects/ai-analytics-evals). The run
step is the reliability skill. This skill is the glue: stage a setup, run reliability, repeat, compute
the delta, restore. The user never types a command; you do each step.
Step 1 - baseline (without the context)
Make sure the baseline is active (the context absent). Use the eval tool's adapter to restore the base dictionary:
import sys; sys.path.insert(0, "<HOME>/projects/ai-analytics-evals")
from aievals.adapters.ai_analyst_plus import AIAnalystPlusAdapter
AIAnalystPlusAdapter().restore()
Then run the reliability check on the question (the /reliability skill: fire N independent sub-agents,
each fresh context, each reporting headline / measured / definition_source). Save the N results to a
run directory, for example .knowledge/comparisons/<question-slug>/<ts>-baseline/runs.json.
Step 2 - with the context
Stage the setup, then run the reliability check again into a second run directory:
AIAnalystPlusAdapter().stage("<the setup dir>") # composes base + the definition overlay
Run reliability again into .../<ts>-with-context/runs.json.
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 · 79 lines · 0 tokens per session scan A 984e410e8763
compare is a skill published in the GitHub repository ai-analyst-lab/ai-analyst-plus (21 stars, last pushed 3mo ago), licensed MIT. It adds 115 tokens to every session and 1,001 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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