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 skills add Tarekkharsa/agentstack --skill analyze-usagegit clone --depth 1 https://github.com/Tarekkharsa/agentstackWrote 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/skills/tarekkharsa/agentstack/analyze-usage)<a href="https://agentmods.dev/skills/tarekkharsa/agentstack/analyze-usage"><img src="https://agentmods.dev/badge/skills/tarekkharsa/agentstack/analyze-usage/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/skills/tarekkharsa/agentstack/analyze-usage"><img src="https://agentmods.dev/badge/skills/tarekkharsa/agentstack/analyze-usage.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 | $0.00045 | $0.00444 |
| Opus 5.5 | $0.00018 | $0.00178 |
| Sonnet 5.5 | $0.00009 | $0.00089 |
| Haiku 4.5 | $0.00005 | $0.00044 |
Grade A, and why
analyze-usage 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.
What it actually says
Analyze usage
Use when you want to understand your own footprint: how many tokens you're burning, and which installed capabilities are actually pulling their weight.
Where the data is
Claude Code writes a JSON-lines transcript per session at:
~/.claude/projects/<project-hash>/<session-id>.jsonl
Each line is one event; assistant turns carry token usage, and tool-use events name the tool or skill invoked. It's local and safe to read.
Token burn
Sum token usage across a session or a day. The fields are nested
(message.usage.input_tokens / output_tokens), so use python for anything
beyond a trivial count — don't hand-roll it in a shell one-liner.
Dead-weight detection (the useful one)
- List what's installed:
agentstack more lib list(library skills + servers) and the project's active profile. - Extract which skills/servers were actually invoked, from the transcripts' tool-use / skill-load events.
- The set difference — installed but never invoked — is dead weight: it taxes every session's context window for nothing. Propose pruning it.
Rules
- Read-only and local. Never send transcript content anywhere; report only aggregates — counts, totals, names.
- Best-effort. The transcript format is undocumented and can change — tolerate unknown lines, don't assume a fixed schema.
- Coverage is uneven. This is rich for Claude Code; other CLIs expose less (or nothing). Say which agents you could actually see.
Note
agentstack records some of this natively (activation counts, per-server context
cost). If agentstack more report calls exists in your version, prefer it — it joins
usage to the library for you. This skill is the portable, no-code version.
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 · 51 lines · 45 tokens per session scan A 94757ec11e3b
analyze-usage is a skill published in the GitHub repository Tarekkharsa/agentstack (3 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 45 tokens to every session and 444 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 2026-08-31.
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