tldr
FeaturedTLDR code analysis — call graphs, semantic search, impact, dataflow, for far fewer tokens than reading the files raw. Triggers "who calls X", "what affects X", "blast radius", before large file reads or refactors.
Install
Quality Score: 90/100
Skill Content
Details
- Author
- darkroomengineering
- Repository
- darkroomengineering/cc-settings
- Created
- 8 months ago
- Last Updated
- today
- Language
- TypeScript
- License
- MIT
Integrates with
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
codeindex
Answer code questions structurally instead of reading whole files. Use when you need to find where something is defined, read one function, see what calls a symbol, trace imports, judge what a change breaks, or orient yourself in an unfamiliar file or repository. Reach for this before Read, Grep or Glob on a code question — and equally before `grep`, `rg`, `cat`, `head`, `sed -n` or `find` in a shell, which is where the same question goes when a harness or permission mode routes file work through Bash. A grep finds a string; it cannot tell you what calls what. Backed by the codeindex MCP server (tree-sitter, 40+ languages).
tokenscope
Judgment-layer review of Claude Code token usage. Use when the user asks to audit token costs, review Claude Code spending, check context waste, or interpret a tokenscope report. Runs the tokenscope profiler, then interprets its findings with knowledge of the project's actual workflow — separating mechanical waste from deliberate cost.
token-efficiency
Token optimization for Claude Code CLI sessions: RTK (Rust Token Killer) command-output compression, efficient file and command strategies, role-based model routing for subagents, Source-of-Truth keyword framework, hybrid SQLite agent memory with checkpoints, and concise output. Use when installing or verifying RTK or its hook, when a dev command's output is large (test runs, builds, installs, long logs), when spawning coding subagents, when writing agent logs or querying agent memory, when seeding a project's SoT keyword index, or when folding agent memory at a checkpoint. Also use when the user mentions 'rtk', 'token efficiency', 'token savings', 'context bloat', 'model routing', 'SoT keywords', or 'checkpoint agent memory', or asks for shorter or less verbose output, or to stop narrating or dumping whole files.