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/rossoctl/examples/wiki-query-clinpx skills add rossoctl/examples --skill wiki-query-cligit clone --depth 1 https://github.com/rossoctl/examplesWhat 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 | $0.00000 | $0.00731 |
| Opus 5 | $0.00000 | $0.00365 |
| Sonnet 5 | $0.00000 | $0.00146 |
| Haiku 4.5 | $0.00000 | $0.00073 |
Grade A, and why
wiki-query-cli 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 yesterday.
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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
kwiki Query Agent (CLI)
Query the wiki memory service using the wiki_cli.py command-line tool.
Prerequisites
The wiki service must be running on http://localhost:8321. Run from the wiki_memory_tool/ directory.
Procedure
1. List Topics
uv run python wiki_cli.py query list-topics
2. List Pages in a Topic
uv run python wiki_cli.py query list-pages {topic_id}
3. Search a Topic
uv run python wiki_cli.py query search {topic_id} "search terms"
Optional: --limit N to control result count.
4. Search All Topics (Global)
uv run python wiki_cli.py query search-all "search terms"
5. Read a Page
uv run python wiki_cli.py query read {topic_id} {path}
Returns page content with frontmatter metadata if present.
6. Activity Feed
uv run python wiki_cli.py query activity # Global
uv run python wiki_cli.py query activity {topic_id} # Topic-specific
7. Backlinks
uv run python wiki_cli.py query backlinks {topic_id} {path}
8. Tags
uv run python wiki_cli.py query tags {topic_id} # List all tags
uv run python wiki_cli.py query tag {topic_id} {tag_name} # Pages by tag
9. Page Graph
uv run python wiki_cli.py query graph {topic_id}
10. Drafts
uv run python wiki_cli.py query drafts {topic_id}
Authentication
GitHub Login (recommended for users)
uv run python wiki_cli.py --base-url https://wiki-service.example.com login
uv run python wiki_cli.py whoami
uv run python wiki_cli.py logout
Once logged in, the CLI uses your GitHub identity for all requests. Token is cached at ~/.wiki-memory/token.json.
SPIFFE Headers (agent mode)
Without a cached token, the CLI uses simulated Query Agent SPIFFE headers with OBO user.
Options
| Flag | Default | Description |
|---|---|---|
--base-url |
http://localhost:8321 |
Service URL |
--user |
[email protected] |
User identity for OBO |
--trust-domain |
rossoctl.example.com |
SPIFFE trust domain |
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.
- yesterday First seen · 121 lines · 0 tokens per session scan A 43b703a4cda5
wiki-query-cli is a skill published in the GitHub repository rossoctl/examples (11 stars, last pushed 4d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 731 tokens. 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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