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 agentmods add skills/frenzymath/danus/query-memorynpx skills add frenzymath/Danus --skill query-memorygit clone --depth 1 https://github.com/frenzymath/DanusWhat 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 | $0.00068 | $0.00761 |
| Opus 5 | $0.00034 | $0.00380 |
| Sonnet 5 | $0.00014 | $0.00152 |
| Haiku 4.5 | $0.00007 | $0.00076 |
Grade A, and why
query-memory 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 3d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Query Memory
Before spending effort, check what already exists. There are three places to look, in the three-memory model:
- Your own local memory (private): read/grep
local_memory/notes.jsonlandevents.jsonlfor your prior reasoning and what you already tried. - Global memory (shared findings):
gm_search(query, kinds=...)over the swarm's findings. Especially useful kinds:dead_end/obstacle— paths that already died (skip them);verification— outcomes of others'fact_submit(learn from rejections);conclusion/example/counterexample/plan— others' results to build on. You can also read theglobal_memory/<kind>.jsonlfiles directly.
- Fact graph (verified truth):
fact_search(query)(BM25 over the verified facts) to find results you can cite or that show your subgoal is already proved — it returns{fact_id, statement}; read the full proof fromfact_graph/facts/<fact_id>.mdon a relevant hit, andfact_graph/glossary.jsonto reuse the project's symbol definitions. A proof may build only on facts (cite afact_id).
Procedure
- Obey the current prompt's restrictions first. If it forbids a direction, file, or search, that overrides default recall. If it recommends specific results or directions, raise their priority.
- Start with the cheapest relevant source: your own local memory for your
context;
gm_searchfor the swarm's findings; the fact graph for verified building blocks. - Prefer a narrow, targeted query (specific
kinds, a sharp query string) over reading everything. - Workspace boundary: stay inside your own working directory and the shared
project stores. Do not scan parent directories, other workers' private
local_memory/, or other projects.
Retrieval priority
- A relevant verified fact (fact graph) is the strongest hit — you can build
on it directly by citing its
fact_id. - A sibling's
dead_end/obstaclesaves you from re-walking a dead path. - A sibling's
verificationrejection tells you why a similar claim failed. - A
conclusion/example/counterexampleis awareness — useful, but never a brick (only facts are). Re-verify anything you intend to build on.
What ships with it
1 file 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.
- 3d ago First seen · 60 lines · 68 tokens per session scan A 17a6355fdf1f
query-memory is a skill published in the GitHub repository frenzymath/Danus (387 stars, last pushed 7d ago), licensed Apache-2.0. It adds 68 tokens to every session and 761 once invoked, about $0.0003 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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