Borrowing it
Nothing to install: this file belongs to VishalJ99/claude-docker. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/VishalJ99/claude-docker/master/.claude/commands/claude-vocab-section.mdgit clone --depth 1 https://github.com/VishalJ99/claude-dockerWrote 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/commands/vishalj99/claude-docker/claude-vocab-section)<a href="https://agentmods.dev/commands/vishalj99/claude-docker/claude-vocab-section"><img src="https://agentmods.dev/badge/commands/vishalj99/claude-docker/claude-vocab-section/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/commands/vishalj99/claude-docker/claude-vocab-section"><img src="https://agentmods.dev/badge/commands/vishalj99/claude-docker/claude-vocab-section.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.00964 |
| Opus 5 | $0.00000 | $0.00482 |
| Sonnet 5 | $0.00000 | $0.00193 |
| Haiku 4.5 | $0.00000 | $0.00096 |
Grade A, and why
claude-vocab-section 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 11d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shared Vocabulary Protocol (add to CLAUDE.md)
Dictionary Location
- Index:
docs/dictionary.md— Load at session start - Full entries:
docs/dictionary/[term].md— Read on-demand
How to Reference
- Load
docs/dictionary.md(the index) at session start - When you encounter a term from the index, read its full entry in
docs/dictionary/ - Use the dictionary definition—NOT your general knowledge
- If a term is missing, follow the process below
When a Term is Missing
If a keyword in the user's query does not exist in the dictionary:
- Flag it: "⚠️ Term '[X]' not found in dictionary"
- Ask the user for a definition or description
- Run
/define-terms "[X]"to create the entry using their input
Do NOT proceed with assumptions. The dictionary exists to prevent guesswork.
When a Potential Match Exists
If a keyword in the user's query is similar to (but not exactly) an existing term:
- Ask for confirmation: "Did you mean '[existing term]'?"
- If yes → use that term's definition
- If it's an alias → update the entry's
Aliasesfield indocs/dictionary/[term].mdto include the user's phrasing
Do NOT
- ❌ Assume you know what a term means without checking
- ❌ Skip the dictionary lookup because a term seems obvious
- ❌ Proceed with ambiguous terms without asking
When Modifying Code
If your changes affect files listed in any dictionary term's "Code Locations":
- Re-read that term's full entry
- Verify your changes align with the defined behavior
- Update the dictionary entry if behavior has changed
Maintenance Responsibility
After ANY code change that:
- Modifies a component/hook/store listed in a dictionary entry
- Introduces a new domain concept
- Changes the behavior of an existing concept
You MUST update docs/dictionary.md accordingly.
The Lookup Pattern
flowchart TD
A[Receive User Instruction] --> B[Scan for Domain-Specific Terms]
B --> C{Term in Dictionary?}
C -->|Exact match| D[Read Full Entry]
C -->|Partial match| E[Ask User: Did you mean X?]
C -->|No match| F[Flag Missing Term]
E -->|Yes| D
E -->|No, it's an alias| G[Update Aliases in Entry]
G --> D
F --> H[Ask User for Definition]
H --> I[Run /define-terms]
I --> D
D --> J[Proceed with Implementation]
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.
- 11d ago First seen · 112 lines · 0 tokens per session scan A 3143ac1c60e0
claude-vocab-section is a command published in the GitHub repository VishalJ99/claude-docker (189 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 964 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.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.