costhq
Track agent session costs, file changes, and git commits with CostHQ. Enforces budget limits, tracks local models, and provides Enterprise SOC2 audit trails via a web dashboard. v3.3.0 - Enterprise SOC2 Audit Logging and Local Models.
Best use case
costhq is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Track agent session costs, file changes, and git commits with CostHQ. Enforces budget limits, tracks local models, and provides Enterprise SOC2 audit trails via a web dashboard. v3.3.0 - Enterprise SOC2 Audit Logging and Local Models.
Teams using costhq should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/costhq/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How costhq Compares
| Feature / Agent | costhq | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Track agent session costs, file changes, and git commits with CostHQ. Enforces budget limits, tracks local models, and provides Enterprise SOC2 audit trails via a web dashboard. v3.3.0 - Enterprise SOC2 Audit Logging and Local Models.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Session Cost Tracking (CostHQ) Track agent session costs, file changes, and git commits. Enforces budget limits, tracks local models (Ollama, vLLM), and provides detailed session analytics with a full web dashboard and tamper-evident SOC2 audit logging for Enterprise users. **Latest: v3.3.0** - Added Enterprise SOC2 Audit Trails and Local Models (compute-time costing). 📦 [npm](https://www.npmjs.com/package/costhq) • ⭐ [GitHub](https://github.com/brian-mwirigi/costhq) • 📝 [Changelog](https://github.com/brian-mwirigi/costhq/blob/main/CHANGELOG.md) ## Installation ```bash # 1. Install the CLI globally from npm npm install -g costhq # 2. Install the OpenClaw skill clawhub install costhq ``` After installing, the `cs` command is available globally. The OpenClaw agent will automatically use it to track sessions. > **Requirements:** Node.js 18+ and C/C++ build tools (needed to compile the embedded SQLite module). > > | OS | Install build tools | > |---|---| > | **Ubuntu/Debian** | `sudo apt-get install -y build-essential python3` | > | **macOS** | `xcode-select --install` | > | **Windows** | `npm install -g windows-build-tools` or install Visual Studio Build Tools | > | **Alpine** | `apk add build-base python3` | > > Data is stored locally at `~/.costhq/sessions.db` (or `~/.CostHQ`). ## When to use - **Always** start a tracked session at the beginning of a multi-step task - **Always** log AI usage after each API call you make - **Always** end the session when the task is complete - Use `cs dashboard` to review session data, set up local models, or verify the audit trail (Enterprise). ## Commands ### Start tracking ```bash # Agent mode (always use --json for structured output): cs start "task description" --json --close-stale # Resume if a session was left open (e.g. after a crash): cs start "task description" --json --resume ``` ### Log AI usage (after each API call) ```bash # Standard cloud model (cost auto-calculated): cs log-ai -p anthropic -m claude-sonnet-4 --prompt-tokens 8000 --completion-tokens 2000 --json # Local model with compute duration (NEW in v3.3.0): # Use --duration in seconds (120) or string (2m30s). Cost is based on registered $/hr rate. cs log-ai -p ollama -m llama3 --tokens 4500 --duration 2m30s --local --json # With all fields: cs log-ai -p openai -m gpt-4o --prompt-tokens 5000 --completion-tokens 1500 -c 0.04 --agent "Research Agent" --json ``` **Agent Name:** Use `--agent "Agent Name"` to track which agent performed the work. **Local Models:** You can track self-hosted models (Ollama, llama.cpp, vLLM) by registering a GPU hourly rate in the dashboard. Use `--duration` and `--local` when logging. ### Check current status ```bash cs status --json ``` ### End session and get summary ```bash cs end -n "completion notes" --json ``` Ending the session automatically logs an audit event (Enterprise) and scans git for files/commits. ### Web Dashboard ```bash cs dashboard ``` The dashboard shows: - **Overview** — KPIs, daily trends, cost velocity. - **Sessions** — searchable/sortable table, per-session details. - **Local Models** — Register compute rates ($/hr) for Ollama, vLLM, etc. - **Compliance** — View the tamper-evident cryptographic SOC2 audit chain and configure Team Identities (Enterprise only). - **Pro Ops** — Manage licensing, PDF exports, and sync features. ### View historical stats and details ```bash cs show --json --files --commits cs stats --json cs export --format json --limit 10 ``` ### Add notes / annotations ```bash cs note "Tests passing, moving to cleanup" --json ``` ## Agent Workflow Agents should **always** use `--json` on every command for structured, parseable output. 1. At task start: `cs start "Fix authentication bug" --json --close-stale` 2. Add context notes: `cs note "analyzing auth flow" --json` 3. After each AI call: `cs log-ai -p anthropic -m claude-sonnet-4 --prompt-tokens 800 --completion-tokens 200 --agent "Bug Fixer" --json` 4. If using a local model: `cs log-ai -p ollama -m mistral --tokens 1000 --duration 45s --local --json` 5. At task end: `cs end -n "Fixed the auth bug" --json` ## Budget & Pricing - Standard pricing is configurable via `cs pricing set my-model 5.00 15.00`. - Local model pricing (compute-based) is configured in the `cs dashboard` under **Local Models**. - Check `cs status --json` before expensive operations. ## Important - **Always** use `--json` on every command — agents must use structured output. - Use `--close-stale` on `cs start` to clear crashed sessions. - In Enterprise mode, a cryptographic hash chain automatically logs session starts, ends, data resets, and AI usage.
Related Skills
workspace-surface-audit
Audit the active repo, MCP servers, plugins, connectors, env surfaces, and harness setup, then recommend the highest-value ECC-native skills, hooks, agents, and operator workflows. Use when the user wants help setting up Claude Code or understanding what capabilities are actually available in their environment.
ui-demo
Record polished UI demo videos using Playwright. Use when the user asks to create a demo, walkthrough, screen recording, or tutorial video of a web application. Produces WebM videos with visible cursor, natural pacing, and professional feel.
token-budget-advisor
Offers the user an informed choice about how much response depth to consume before answering. Use this skill when the user explicitly wants to control response length, depth, or token budget. TRIGGER when: "token budget", "token count", "token usage", "token limit", "response length", "answer depth", "short version", "brief answer", "detailed answer", "exhaustive answer", "respuesta corta vs larga", "cuántos tokens", "ahorrar tokens", "responde al 50%", "dame la versión corta", "quiero controlar cuánto usas", or clear variants where the user is explicitly asking to control answer size or depth. DO NOT TRIGGER when: user has already specified a level in the current session (maintain it), the request is clearly a one-word answer, or "token" refers to auth/session/payment tokens rather than response size.
skill-comply
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines
santa-method
Multi-agent adversarial verification with convergence loop. Two independent review agents must both pass before output ships.
safety-guard
Use this skill to prevent destructive operations when working on production systems or running agents autonomously.
repo-scan
Cross-stack source code asset audit — classifies every file, detects embedded third-party libraries, and delivers actionable four-level verdicts per module with interactive HTML reports.
project-flow-ops
Operate execution flow across GitHub and Linear by triaging issues and pull requests, linking active work, and keeping GitHub public-facing while Linear remains the internal execution layer. Use when the user wants backlog control, PR triage, or GitHub-to-Linear coordination.
product-lens
Use this skill to validate the "why" before building, run product diagnostics, and pressure-test product direction before the request becomes an implementation contract.
openclaw-persona-forge
为 OpenClaw AI Agent 锻造完整的龙虾灵魂方案。根据用户偏好或随机抽卡, 输出身份定位、灵魂描述(SOUL.md)、角色化底线规则、名字和头像生图提示词。 如当前环境提供已审核的生图 skill,可自动生成统一风格头像图片。 当用户需要创建、设计或定制 OpenClaw 龙虾灵魂时使用。 不适用于:微调已有 SOUL.md、非 OpenClaw 平台的角色设计、纯工具型无性格 Agent。 触发词:龙虾灵魂、虾魂、OpenClaw 灵魂、养虾灵魂、龙虾角色、龙虾定位、 龙虾剧本杀角色、龙虾游戏角色、龙虾 NPC、龙虾性格、龙虾背景故事、 lobster soul、lobster character、抽卡、随机龙虾、龙虾 SOUL、gacha。
manim-video
Build reusable Manim explainers for technical concepts, graphs, system diagrams, and product walkthroughs, then hand off to the wider ECC video stack if needed. Use when the user wants a clean animated explainer rather than a generic talking-head script.
laravel-plugin-discovery
Discover and evaluate Laravel packages via LaraPlugins.io MCP. Use when the user wants to find plugins, check package health, or assess Laravel/PHP compatibility.