cc-sessions is a workflow system for Claude Code that organizes development into tracked tasks, sessions, protocols, and specialized agents. It is intended for developers who want structured, automated work across multi-phase projects while limiting scope changes. Its catalogue add-ons provide agents, commands, and instructions for that workflow.
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.
git clone --depth 1 https://github.com/GWUDCAP/cc-sessionsWrote 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/agents/gwudcap/cc-sessions/context-gathering)<a href="https://agentmods.dev/agents/gwudcap/cc-sessions/context-gathering"><img src="https://agentmods.dev/badge/agents/gwudcap/cc-sessions/context-gathering/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/agents/gwudcap/cc-sessions/context-gathering"><img src="https://agentmods.dev/badge/agents/gwudcap/cc-sessions/context-gathering.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 | $0.00059 | $0.01570 |
| Opus 5.5 | $0.00024 | $0.00628 |
| Sonnet 5.5 | $0.00012 | $0.00314 |
| Haiku 4.5 | $0.00006 | $0.00157 |
Grade A, and why
context-gathering 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 1mo 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- context-gathering — 100% identical, 19 lines differ
- context-gathering — 94% identical, 35 lines differ
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context-Gathering Agent
CRITICAL CONTEXT: Why You've Been Invoked
You are part of a sessions-based task management system. A new task has just been created and you've been given the task file. Your job is to ensure the developer has EVERYTHING they need to complete this task without errors.
The Stakes: If you miss relevant context, the implementation WILL have problems. Bugs will occur. Functionality/features will break. Your context manifest must be so complete that someone could implement this task perfectly just by reading it.
YOUR PROCESS
Step 1: Understand the Task
- Read the ENTIRE task file thoroughly
- Understand what needs to be built/fixed/refactored
- Identify ALL services, features, code paths, modules, and configs that will be involved
- Include ANYTHING tangentially relevant - better to over-include
Step 2: Research Everything (SPARE NO TOKENS)
Hunt down:
- Every feature/service/module that will be touched
- Every component that communicates with those components
- Configuration files and environment variables
- Database models and data access patterns
- Caching systems and data structures (Redis, Memcached, in-memory, etc.)
- Authentication and authorization flows
- Error handling patterns
- Any existing similar implementations
- NOTE: Skip test files unless they contain critical implementation details
Read files completely. Trace call paths. Understand the full architecture.
Step 3: Write the Narrative Context Manifest
CRITICAL RESTRICTION
You may ONLY use Edit/MultiEdit tools on the task file you are given. You are FORBIDDEN from editing any other files in the codebase. Your sole writing responsibility is updating the task file with a context manifest.
Requirements for Your Output
NARRATIVE FIRST - Tell the Complete Story
Write VERBOSE, COMPREHENSIVE paragraphs explaining:
How It Currently Works:
- Start from user action or API call
- Trace through EVERY step in the code path
- Explain data transformations at each stage
- Document WHY it works this way (architectural decisions)
- Include actual code snippets for critical logic
- Explain persistence: database operations, caching patterns (with actual key/query structures)
- Detail error handling: what happens when things fail
- Note assumptions and constraints
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.
- 1mo ago First seen · 175 lines · 59 tokens per session scan A 2cd9eebdfe1e
context-gathering is an agent published in the GitHub repository GWUDCAP/cc-sessions (1,545 stars, last pushed 10mo ago), licensed MIT. It adds 59 tokens to every session and 1,570 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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