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 commands/xsaven/vector-memory-mcp/workgit clone --depth 1 https://github.com/Xsaven/vector-memory-mcpWhat 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 | $0.00013 | $0.06788 |
| Opus 5 | $0.00006 | $0.03394 |
| Sonnet 5 | $0.00003 | $0.01358 |
| Haiku 4.5 | $0.00001 | $0.00679 |
Grade A, and why
doc:work 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 — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Iron Rules
No-hallucination (CRITICAL)
NEVER output results without ACTUALLY calling tools. You CANNOT know task status or content without REAL tool calls. Fake results = CRITICAL VIOLATION.
No-verbose (CRITICAL)
FORBIDDEN: Wrapping actions in verbose commentary blocks (meta-analysis, synthesis, planning, reflection) before executing. Act FIRST, explain AFTER.
Max-interactivity (CRITICAL)
When $HAS_AUTO_APPROVE = false: MUST engage user with clarifying questions via AskUserQuestion tool. NEVER assume scope, depth, audience, or structure. Documentation is a COLLABORATIVE process — user defines WHAT, agent researches and writes HOW. When $HAS_AUTO_APPROVE = true: infer scope/depth/audience from $CLEAN_ARGS context. Skip clarifying questions. Proceed autonomously through all phases.
- why: Wrong assumptions about documentation scope = useless output + full rework. Interactive alignment is cheaper than rewrites. But -y flag means user trusts agent to make reasonable decisions autonomously.
- on_violation: If interactive: STOP and ask clarifying question. If auto-approve: infer from input and proceed.
Discovery-before-creation (CRITICAL)
ALWAYS search existing docs via brain docs CLI BEFORE creating new files. Flow: brain docs "{keywords}" → found? → READ existing → UPDATE. Not found? → apply aggressive-docs-search (3+ keyword variations). Still not found → CREATE new. NEVER create duplicate documentation for same topic.
- why: Duplicate docs diverge over time. One source of truth per topic. Updating existing is faster and preserves history.
- on_violation: Run brain docs first. Found → update. Not found after 3+ searches → create new.
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 · 328 lines · 13 tokens per session scan A c137c4481b97
doc:work is a command published in the GitHub repository Xsaven/vector-memory-mcp (0 stars, last pushed 6mo ago), licensed MIT. It adds 13 tokens to every session and 6,788 once invoked, about $0.0001 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 2026-09-01.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.