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/consiliency/code-index-mcp/find-symbolgit clone --depth 1 https://github.com/Consiliency/Code-Index-MCPWrote 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/consiliency/code-index-mcp/find-symbol)<a href="https://agentmods.dev/commands/consiliency/code-index-mcp/find-symbol"><img src="https://agentmods.dev/badge/commands/consiliency/code-index-mcp/find-symbol.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 | $0.00000 | $0.00242 |
| Opus 5 | $0.00000 | $0.00121 |
| Sonnet 5 | $0.00000 | $0.00048 |
| Haiku 4.5 | $0.00000 | $0.00024 |
Grade A, and why
find-symbol 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 4d 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.
What it actually says
Find Symbol Definition
Quickly locate any symbol (class, function, method, variable) in the codebase using the MCP index.
Use indexed results as authoritative only when repository readiness is ready.
If symbol_lookup returns index_unavailable with
safe_fallback: "native_search", use native rg/file search and follow the
readiness remediation, such as reindex.
Usage
/find-symbol <symbol_name>
Examples
/find-symbol PluginManager- Find the PluginManager class/find-symbol process_file- Find the process_file function/find-symbol IndexDiscovery- Find the IndexDiscovery class
Implementation
This command uses mcp__code-index-mcp__symbol_lookup to instantly locate symbol definitions.
Benefits:
- Speed: <100ms lookup time
- Accuracy: Exact definition location with line numbers
- Context: Returns signature and documentation
Ready indexes return ordinary result: "not_found" for misses. Non-ready
indexes return index_unavailable, where native_search is expected until
remediation is complete.
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.
- 4d ago First seen · 30 lines · 0 tokens per session scan A ec976cd60e5d
find-symbol is a command published in the GitHub repository Consiliency/Code-Index-MCP (57 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 242 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
git
Git operations with intelligent commit messages and workflow optimization.
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.
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.