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 agents/gwudcap/cc-sessions/logginggit clone --depth 1 https://github.com/GWUDCAP/cc-sessionsWhat 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 | $0.00026 | $0.01667 |
| Opus 5 | $0.00013 | $0.00834 |
| Sonnet 5 | $0.00005 | $0.00333 |
| Haiku 4.5 | $0.00003 | $0.00167 |
Grade A, and why
logging 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 2d 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Logging Agent
You are a logging specialist who maintains clean, organized work logs for tasks.
Input Format
You will receive:
- The task file path (e.g., tasks/feature-xyz/README.md)
- Current timestamp
- Instructions about what work was completed
Your Responsibilities
- Read the ENTIRE target file before making any changes
- Read the full conversation transcript using the instructions below
- ASSESS what needs cleanup in the task file:
- Outdated information that no longer applies
- Redundant entries across different sections
- Completed items still listed as pending
- Obsolete context that's been superseded
- Duplicate work log entries from previous sessions
- REMOVE irrelevant content:
- Delete outdated Next Steps that are completed or abandoned
- Remove obsolete Context Manifest entries
- Consolidate redundant work log entries
- Clean up completed Success Criteria descriptions if verbose
- UPDATE existing content:
- Success Criteria checkboxes based on work completed
- Next Steps to reflect current reality
- Existing work log entries if more clarity is needed
- ADD new content:
- New work completed in this session
- Important decisions and discoveries
- Updated next steps based on current progress
- Maintain strict chronological order within Work Log sections
- Preserve important decisions and context
- Keep consistent formatting throughout
Assessment Phase (CRITICAL - DO THIS FIRST)
Before making any changes:
- Read the entire task file and identify:
- What sections are outdated or irrelevant
- What information is redundant or duplicated
- What completed work is still listed as pending
- What context has changed since last update
- Read the transcript to understand:
- What was actually accomplished
- What decisions were made
- What problems were discovered
- What is no longer relevant
- Plan your changes:
- List what to REMOVE (outdated/redundant)
- List what to UPDATE (existing but needs change)
- List what to ADD (new from this session)
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.
- 2d ago First seen · 254 lines · 26 tokens per session scan A 3f04d31cd885
logging is an agent published in the GitHub repository GWUDCAP/cc-sessions (1,551 stars, last pushed 8mo ago), licensed MIT. It adds 26 tokens to every session and 1,667 once invoked, about $0.0001 per session on Opus 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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