Context Builder: Codebase-to-LLM Context Generator

VerifiedSafe

Generate a structured markdown file from any codebase for LLM consumption. Orchestrate agent handoffs for senior one-shot reviews.

Sby Skills Guide Bot
DevelopmentIntermediate
9/4/2026
Claude CodeCursorCodex
#llm-context#codebase-packaging#code-review#token-budgeting#multi-agent-orchestration

Recommended for

Automated summary

Packages a codebase directory into a single structured markdown file tuned for LLM consumption, and orchestrates the Deep Think Authority pipeline (context → Deep Think review → agent execution).

Strengths

  • Ranks files by relevance and extracts AST signatures via tree-sitter, giving compact yet structurally meaningful context
  • Automatic token budgeting with extension filters (-f) and built-in exclusions (.git, node_modules, .gitignore rules, binary sniffing)
  • Ships a multi-model workflow that binds a tool-using agent (Flash, Antigravity) to an AUTHORITY document produced by a stronger reasoning pass
  • Handles several real jobs: architecture review, onboarding, diff-based refresh, and packaging a dependency's source

Limitations

  • Installs through cargo and requires a Rust toolchain, unless you fetch a prebuilt binary manually
  • Generated output can carry API keys or credentials found in source files, so manual review is mandatory
  • The Deep Think Authority pipeline relies on an external Deep Think model and a specific agent harness that the binary does not provide
When to use it

Reach for it when a model needs a whole-repo view at a sane token cost, or when you want a weaker coding agent constrained by a formalized senior review.

When not to use it

Avoid it on home directories, system paths, or credential stores, and don't expect it to produce its own static-analysis findings rather than raw context.

Security analysis

Safe
Quality score82/100

This is a documentation skill for an external Rust CLI. Installation is a standard `cargo install` (not curl|sh or obfuscated), there are no destructive commands, no exfiltration, no base64 payloads, and no attempts to disable safety. It actually embeds solid security guardrails: targeting explicit project roots, using scoped `-f` filters, avoiding credential stores, and reviewing output for secrets. The only residual risk is that packaged output can contain embedded secrets, which the skill explicitly warns about.

Findings
  • •The generated context output may embed secrets/credentials found in source files; the skill acknowledges this and advises review/gitignore exclusion, but users must heed it
  • •Skill packages arbitrary directory file contents for downstream LLM processing, so path-scoping discipline matters (skill explicitly warns against ~, /, ~/.ssh, ~/.aws, /etc)
How this analysis is made

Examples

Package a repo for review
Run context-builder on /home/user/projects/myapp, restrict it to rs,toml,md files, and write the result to docs/context.md.
Deep Think handoff
Generate the context for this repository, prepare a Deep Think review packet from it, then bind the implementation agent to the resulting AUTHORITY document.
Diff-based refresh
Since the last context build I've made several commits — regenerate only the diffs so the LLM's understanding of the project stays current.

name: context-builder description: > Package codebases into LLM-optimized markdown, and run the Deep Think Authority pipeline (context-builder → Deep Think review → structured AUTHORITY → Flash/Antigravity implementation agent). Use when generating project context, preparing Deep Think reviews, or binding a weaker coding agent to a senior reasoning pass. homepage: https://github.com/igorls/context-builder version: 0.10.0 requires:

  • context-builder

Context Builder — Agentic Skill

Generate a single, structured markdown file from any codebase directory. The output is optimized for LLM consumption with relevance-based file ordering, AST-aware code signatures, automatic token budgeting, and smart defaults.

Also: orchestrate the Deep Think Authority handoff so tool-using agents (Antigravity, Gemini Flash, etc.) implement senior one-shot reviews instead of freelancing. Full harness: docs/agent-harness/.

Installation

# Requires Rust toolchain. Builds from source with cryptographic verification via crates.io.
cargo install context-builder --features tree-sitter-all

Pre-built binaries with SHA256 checksums are also available for manual download from GitHub Releases.

Verify: context-builder --version (expected: 0.10.0)

Security & Path Scoping

IMPORTANT: This tool reads file contents from the specified directory. Agents MUST follow these rules:

  • Only target explicit project directories — always pass the exact project root (e.g., /home/user/projects/myapp). Never point at home directories, system paths, or credential stores (~/.ssh, ~/.aws, /etc, ~, /)
  • Use scoped filters — use -f to limit to known source extensions (e.g., -f rs,toml,md), reducing exposure surface
  • Output to project-local paths — write output to the project's docs/ folder or /tmp/, never to shared or public locations
  • Review before sharing — the output may contain API keys, secrets, or credentials embedded in source files; always review or use .gitignore patterns to exclude sensitive files

Built-in protections (always active, no configuration needed):

  • Excludes .git/, node_modules/, and 19 other heavy/sensitive directories at any depth
  • Respects .gitignore rules when a .git directory is present
  • Binary files are auto-detected and skipped via UTF-8 sniffing
  • Output file and cache directory are auto-excluded to prevent self-ingestion

When to Use

  • Deep code review — Feed an entire codebase to an LLM for architecture analysis or bug hunting
  • Deep Think → agent pipeline — Package context for Ultra Deep Think, then bind Antigravity/Flash to the resulting AUTHORITY document
  • Onboarding — Generate a project snapshot for understanding unfamiliar codebases
  • Diff-based updates — After code changes, generate only the diffs to update an LLM's understanding
  • AST signatures — Extract function/class signatures for token-efficient structural understanding
  • Cross-project research — Quickly package a dependency's source for analysis

Deep Think Authority Pipeline (primary multi-model workflow)

Weak agent harnesses (e.g. Gemini Flash in Antigravity) are strong at tools and weak at novel reasoning. Deep Think (Ultra web) is the inverse. Do not try to make Flash invent architecture. Inject Deep Think as law, then let Flash execute.

context-builder  →  Deep Think (AUTHORITY)  →  Agent BUILD  →  RESULT
                         ↑                         │
                         └──── CONFLICT / DEBUG ────┘

Agent rules (always)

  1. AUTHORITY is law — do not redesign, re-prioritize, or “improve” beyond the packet
  2. Stop on conflict — if the live repo contradicts AUTHORITY, emit CONFLICT; do not freestyle
  3. Do not re-inject the full context dump into the agent — Deep Think already distilled it; the agent should use tools on the real tree
  4. Prefer a tight AUTHORITY (≈2–4k tokens): verdict, ordered file-level steps, verification commands
  5. Verification is mandatory before DONE

Step-by-step

# 0) Size check
context-builder -d /abs/path/to/project --token-count

# 1) Package for Deep Think (adjust -f to the language)
mkdir -p docs/handoffs/$(date +%Y-%m-%d)-topic
context-builder -d /abs/path/to/project \
  -f rs,toml,md \
  --max-tokens 120000 \
  -y -o docs/handoffs/$(date +%Y-%m-%d)-topic/00-context.md
  1. Deep Think (Ultra web): attach 00-context.md, paste docs/agent-harness/templates/01-problem.md, require AUTHORITY shape from 02-authority.md.
  2. Human: trim fluff → save 02-authority.md (budget beats volume for Flash).
  3. Agent: load system prompt from docs/agent-harness/antigravity-system-prompt.md; paste 03-build.md with AUTHORITY inlined or path-referenced.
  4. Agent returns RESULT (04-result.md) or CONFLICT (05-conflict.md).
  5. Optional second Deep Think pass: context-builder -d ... -y --diff-only after implementation.

Harness overview, attention budget, and re-escalation table: docs/agent-harness/README.md.

What this changes about Flash’s behavior

| Without AUTHORITY | With engineered AUTHORITY | | --- | --- | | Invents architecture mid-task | Executes ordered steps | | Thrash-refactors “while here” | Surgical diffs only | | Vague “done” | Verification commands required | | Silent plan failure | CONFLICT stop → re-escalate |

It does not give Flash Deep Think’s raw intelligence. It meaningfully raises implementation fidelity when AUTHORITY is high quality.

Core Workflow

1. Quick Context (whole project)

context-builder -d /path/to/project -y -o context.md
  • -y skips confirmation prompts (recommended for agent workflows when path is explicitly scoped)
  • Output includes: header → file tree → files sorted by relevance (config → source → tests → docs)

2. Scoped Context (specific file types)

context-builder -d /path/to/project -f rs,toml -i docs,assets -y -o context.md
  • -f rs,toml includes only Rust and TOML files
  • -i docs,assets excludes directories by name

3. AST Signatures Mode (minimal tokens)

context-builder -d /path/to/project --signatures -f rs,ts,py -y -o signatures.md
  • Replaces full file content with extracted function/class signatures (~4K vs ~15K tokens per file)
  • Supports 8 languages: Rust, JavaScript (.js/.jsx), TypeScript (.ts/.tsx), Python, Go, Java, C, C++
  • Requires --features tree-sitter-all at install time

4. Signatures with Structural Summary

context-builder -d /path/to/project --signatures --structure -y -o context.md
  • --structure appends a count summary (e.g., "6 functions, 2 structs, 1 impl block")
  • Combine with --visibility public to show only public API surface

5. Budget-Constrained Context

context-builder -d /path/to/project --max-tokens 100000 -y -o context.md
  • Caps output to ~100K tokens (estimated)
  • Files are included in relevance order until budget is exhausted
  • Automatically warns if output exceeds 128K tokens

6. Token Count Preview

context-builder -d /path/to/project --token-count
  • Prints estimated token count without generating output
  • Use this first to decide if filtering or --signatures is needed

7. Incremental Diffs

First, ensure context-builder.toml exists with:

timestamped_output = true
auto_diff = true

Then run twice:

# First run: baseline snapshot
context-builder -d /path/to/project -y

# After code changes: generates diff annotations
context-builder -d /path/to/project -y

For minimal output (diffs only, no full file bodies):

context-builder -d /path/to/project -y --diff-only

Smart Defaults

These behaviors require no configuration:

| Feature | Behavior | |---------|----------| | Auto-ignore | node_modules, dist, build, __pycache__, .venv, vendor, and 12 more heavy dirs are excluded at any depth | | Self-exclusion | Output file, cache dir, and context-builder.toml are auto-excluded | | .gitignore | Respected automatically when .git directory exists | | Binary detection | Binary files are skipped via UTF-8 sniffing | | File ordering | Config/docs first → source (entry points before helpers) → tests → build/CI → lockfiles |

CLI Reference (Agent-Relevant Flags)

| Flag | Purpose | Agent Guidance | |------|---------|----------------| | -d <PATH> | Input directory | Always use absolute paths for reliability | | -o <FILE> | Output path | Write to project docs/ or /tmp/ | | -f <EXT> | Filter by extension | Comma-separated: -f rs,toml,md | | -i <NAME> | Ignore dirs/files | Comma-separated: -i tests,docs,assets | | --max-tokens <N> | Token budget cap | Use 100000 for most models, 200000 for Gemini | | --token-count | Dry-run token estimate | Run first to check if filtering is needed | | -y | Skip all prompts | Use only with explicit, scoped project paths | | --preview | Show file tree only | Quick exploration without generating output | | --diff-only | Output only diffs | Minimizes tokens for incremental updates | | --signatures | AST signature extraction | Requires tree-sitter-all feature at install | | --structure | Structural summary | Pair with --signatures for compact output | | --visibility <V> | Filter by visibility | all (default), public (public API only) | | --truncate <MODE> | Truncation strategy for --max-tokens | smart (AST-aware) or byte | | --init | Create config file | Auto-detects project file types | | --clear-cache | Reset diff cache | Use if diff output seems stale |

Recipes

Recipe: Deep Think Code Review (one-shot only)

context-builder -d /path/to/project -f rs,toml --max-tokens 120000 -y -o docs/deep_think_context.md
# Attach to Deep Think + a structured review prompt (see docs/research/prompts/)

For review → implement (Deep Think then Antigravity), use the Deep Think Authority Pipeline above, not a freeform paste.

Recipe: API Surface Review (signatures only)

# Extract only public signatures — typically 80-90% fewer tokens than full source
context-builder -d /path/to/project --signatures --visibility public -f rs -y -o docs/api_surface.md

Recipe: Compare Two Versions

# Generate context for both versions
context-builder -d ./v1 -f py -y -o /tmp/v1_context.md
context-builder -d ./v2 -f py -y -o /tmp/v2_context.md

# Feed both to an LLM for comparative analysis

Recipe: Monorepo Slice

# Focus on a specific package within a monorepo
context-builder -d /path/to/monorepo/packages/core -f ts,tsx -i __tests__,__mocks__ -y -o core_context.md

Recipe: Quick Size Check Before Deciding Strategy

# Check if the project fits in context
context-builder -d /path/to/project --token-count

# If > 128K tokens, try signatures mode first:
context-builder -d /path/to/project --signatures --token-count

# Or scope it down:
context-builder -d /path/to/project -f rs,toml --max-tokens 100000 --token-count

Configuration File (Optional)

Create context-builder.toml in the project root for persistent settings:

output = "docs/context.md"
output_folder = "docs"
filter = ["rs", "toml"]
ignore = ["target", "benches"]
timestamped_output = true
auto_diff = true
max_tokens = 120000
signatures = true
structure = true
visibility = "public"

Initialize one automatically with context-builder --init.

Output Format

The generated markdown follows this structure:

# Directory Structure Report
[metadata: project name, filters, content hash]

## File Tree
[visual tree of included files]

## Files
### File: src/main.rs
[code block with file contents, syntax-highlighted by extension]

### File: src/lib.rs
...

Files appear in relevance order (not alphabetical), prioritizing config and entry points so LLMs build understanding faster.

When --signatures is active, file contents are replaced with extracted signatures:

### File: src/lib.rs
```rust
pub fn run_with_args(args: Args, config: Config, prompter: &dyn Prompter) -> Result<()>
pub fn generate_markdown_with_diff(...) -> Result<String>
```

Error Handling

  • If context-builder is not installed, install with cargo install context-builder --features tree-sitter-all
  • If --signatures shows no output for a file, the language may not be supported or the feature was not enabled at install
  • If output exceeds token limits, add --max-tokens or narrow with -f / -i, or use --signatures
  • If the project has no .git directory, auto-ignores still protect against dependency flooding
  • Use --clear-cache if diff output seems stale or incorrect

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/context-builder-codebase-to-llm-context-generator-mtmi9aml/download' --output '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md.part' && mv '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md.part' '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Original excerpt: Installation
# Requires Rust toolchain. Builds from source with cryptographic verification via crates.io.
cargo install context-builder --features tree-sitter-all

Pre-built binaries with SHA256 checksums are also available for manual download from GitHub Releases.

Verify: context-builder --version (expected: 0.10.0)

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md' && test -s '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/context-builder' && cp -R '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml' '.claude/skills/context-builder'

Cursor
test -f '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md' && test -s '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md' && mkdir -p '.cursor/skills' && test ! -e '.cursor/skills/context-builder' && cp -R '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml' '.cursor/skills/context-builder'

Codex
test -f '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md' && test -s '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md' && mkdir -p '.agents/skills' && test ! -e '.agents/skills/context-builder' && cp -R '.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml' '.agents/skills/context-builder'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml'

openskills read 'context-builder-codebase-to-llm-context-generator-mtmi9aml'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/context-builder-codebase-to-llm-context-generator-mtmi9aml/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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