Skill Detail

Track Coding-Agent Work Evidence With agentacct

Create a local dashboard that joins coding-agent session logs, token estimates, recorded work steps, and verification checks into reviewable task evidence.

Developer ToolsMulti-Framework
Developer Tools Multi-Framework Security Reviewed
⭐ 537 GitHub stars
INSTALL WITH ANY AGENT
npx skills add agentskillexchange/skills --skill track-coding-agent-work-evidence-with-agentacct Copy
Works best when you want a reusable capability, not another fragile one-off prompt.
At a glance
Tools required
Python 3.11 or newer; agentacct CLI; local coding-agent session logs; optional MCP tools/hooks installed by onboarding
Install & setup
Install with pipx install agentacct, then run agentacct onboard. The README also documents uv tool install agentacct and venv fallback options.
Author
Mike Hasa
Publisher
Individual
Last updated
Jul 30, 2026
Quick brief

Use agentacct when an operator needs a local audit trail for what coding agents did, what evidence they recorded, and what the run likely cost. The workflow is to install agentacct, run onboarding once per machine or project, let it detect local Claude Code and Codex session logs, and then use the local dashboard plus MCP recording tools to inspect tasks, sections, machine checks, token counts, cost estimates, and attribution confidence. This is useful after multi-agent work, client-billable coding sessions, or team reviews where a transcript alone is too noisy and a token counter alone is too thin. Invoke it instead of reading raw client logs when the question is which task consumed resources, which checks passed, and how strongly each usage record maps to the work. The scope boundary is local-first coding-agent observability and evidence review. It is not a cloud billing system, provider invoice source, generic analytics platform, or broad LLM observability SDK.