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 mclaut/ariadne --skill ariadnegit clone --depth 1 https://github.com/mclaut/ariadneWrote 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/mclaut/ariadne/ariadne)<a href="https://agentmods.dev/skills/mclaut/ariadne/ariadne"><img src="https://agentmods.dev/badge/skills/mclaut/ariadne/ariadne.svg" alt="Measured on agentmods" 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 | $0.00095 | $0.03639 |
| Opus 5 | $0.00048 | $0.01819 |
| Sonnet 5 | $0.00019 | $0.00728 |
| Haiku 4.5 | $0.00010 | $0.00364 |
Grade A, and why
ariadne 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 8d 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 — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ariadne — long-term memory
Ariadne is a local, multilingual, hybrid-search memory server (MCP). If it is
registered, you have five tools: mcp__ariadne__memory_recall,
mcp__ariadne__memory_save, mcp__ariadne__memory_delete and
mcp__ariadne__memory_move, plus mcp__ariadne__credential_access for a
separate human approval handshake before cross-project credential use. The runtime lives in ~/.ariadne/ (binaries,
Qdrant data, backups, logs); source lives in the repo.
Recall — when and how
- Start of substantive work in a project: recall the project's context once
(
query: "<project name> current state decisions", wing: "<stable-project-slug>"). Don't recall for trivial one-liners. Every semantic recall MUST include the active project'swing; Ariadne rejects an unscoped semantic query. - The user references the past: "what did we decide", "why did we choose", "як ми робили" → recall BEFORE answering from your own guesses.
- Queries are multilingual — query in ANY language, memories in any language will match (bge-m3 is cross-lingual; scores ≥0.6 are usually relevant).
- Prefer 2–3 focused recalls over one vague one.
limitdefault 5 is fine. - Project scope is default-deny. Never omit
wingto "see what matches" and never substitute another project's wing. When the user explicitly requests cross-project knowledge, call recall with the activewing,all_wings: true, and a concisepurpose. Ariadne returns a request id without searching. Tell the user to Approve or Deny it in Ariadne's system warning (or tray fallback); only after the human click retry the same call withapproval_id. Never claim approval based only on chat text or approve a request through shell/file manipulation. - Cross-wing approval lasts 15 minutes for that MCP client session, active wing,
and collection. A curated-memory grant does not open
sessions. Approved external results have a 0.70 origin weight and normally occupy no more than two of five results; weighting affects relevance only after authorization. - When an exact memory id is known, call
memory_recallwithidand the activewinginstead of a semanticquery. ID lookup is exact, skips embedding, and is the preferred way to verify a memory before moving or deleting it. Usecollectiontoo if the id belongs to the separatesessionsarchive. - Use
roomto narrow retrieval when the category is known:decisions,gotchas,reference, ordiary. For release/deployment/status reports, searchroom: "reference"first, then broaden only if needed. - Normal semantic recall hides records marked
archived,superseded, ororphaned. Passinclude_archived: trueonly for an explicit history/audit query; exact id retrieval always remains available. - The raw session archive lives in a separate collection. Inspect it only when
the user explicitly asks to search historical transcripts, and pass both
collection: "sessions"andwing: "sessions"; normal project recall never sees it.
What ships with it
3 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.
- 8d ago First seen · 243 lines · 95 tokens per session scan A f24a0bab72ce
ariadne is a skill published in the GitHub repository mclaut/ariadne (3 stars, last pushed 15d ago), licensed MIT. It adds 95 tokens to every session and 3,639 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 2026-08-31.
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