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 archaeologygit 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/archaeology)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/archaeology"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/archaeology/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/archaeology"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/archaeology.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 | $0.00100 | $0.01315 |
| Opus 5 | $0.00050 | $0.00658 |
| Sonnet 5 | $0.00020 | $0.00263 |
| Haiku 4.5 | $0.00010 | $0.00131 |
Grade A, and why
archaeology 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 9d 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Query Archaeology
Purpose
Retrieve proven SQL patterns, table cheatsheets, and join patterns from the query archaeology store so agents reuse validated work instead of writing SQL from scratch. The skill also defines the store's local write path: after a validated analysis, the final SQL is curated back into the store (the Writer Convention below), which is what makes the retrieval loop close.
When to Use
- Automatically before any analysis agent writes SQL (pre-flight step)
- Manually when the user asks about known patterns for a table or join
- After a validated analysis, to curate the proven SQL (Writer Convention)
Instructions
Step 1: Check the Index
Read .knowledge/query-archaeology/curated/index.yaml. Parse counters:
cookbook_entries, table_cheatsheets, join_patterns.
If all three are zero (or the file is missing), stop here. Return nothing and do not mention archaeology to the user.
Step 2: Identify Search Terms
From the current analysis context, extract:
- Table names the agent is about to query (e.g.,
orders,events) - Query intent tags (e.g.,
funnel,retention,revenue,cohort)
Step 3: Search the Three Stores
Search each store that has entries (per index counts). Match using
case-insensitive substring -- order matches orders, order_items.
3a. Cookbook (curated/cookbook/*.yaml)
For each file, check:
tablesarray -- any element contains a search table name as substring?tagsarray -- any element matches a query intent tag?
Extract on match: title, sql, tables, tags, and any caveats/notes.
3b. Table Cheatsheets (curated/tables/*.yaml)
For each file, check:
table_namecontains a search table name as substring?
Extract on match: table_name, grain, primary_key, common_filters,
gotchas, common_joins.
3c. Join Patterns (curated/joins/*.yaml)
For each file, check:
tablesarray -- at least two elements match search table names?- If only one search table, match if
tablescontains it as substring.
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.
- 9d ago First seen · 139 lines · 100 tokens per session scan A f576e9e3b62a
archaeology is a skill published in the GitHub repository ai-analyst-lab/ai-analyst-plugin (32 stars, last pushed 13d ago), licensed MIT. It adds 100 tokens to every session and 1,315 once invoked, about $0.0005 per session on Opus 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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