Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/egorfedorov/claude-context-optimizernpx agentmods add skills/egorfedorov/claude-context-optimizer/cco-toolsWrote 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/egorfedorov/claude-context-optimizer/cco-tools)<a href="https://agentmods.dev/skills/egorfedorov/claude-context-optimizer/cco-tools"><img src="https://agentmods.dev/badge/skills/egorfedorov/claude-context-optimizer/cco-tools.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00027 | $0.00419 |
| Opus 5 | $0.00014 | $0.00210 |
| Sonnet 5 | $0.00005 | $0.00084 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
cco-tools 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 8d 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
CCO Tools — what your tools really cost
MCP and Agent token costs used to be constants picked once (mcp__* ≈ 200 in,
Agent ≈ 500). Real results vary by orders of magnitude — a "list all issues"
query and a one-row lookup are the same tool name and nowhere near the same
cost. On MCP-heavy sessions the budget meter was guessing at its biggest line
item.
CCO now measures every tool result and learns the average per tool name.
Run from the plugin root:
show (or no arguments)
node src/tool-costs.js
Prints the learned table: calls, average, worst case, and cumulative total per tool, sorted by total spend.
When reading it back to the user, the useful observations are:
- The top row by
totalis where their context budget actually goes. It is frequently an MCP server rather than file reads. - A row marked
·has fewer than 3 samples and is still using the built-in constant — its estimate isn't trustworthy yet. - A large gap between
avgandmaxmeans that tool is unpredictable; suggest narrowing its queries (filters, limits, pagination) rather than dropping it.
Pair with /cco-overhead mcp — that shows which servers are configured but
never called; this shows what the called ones actually cost.
reset
node src/tool-costs.js reset
Clears the learned table and returns every tool to its built-in constant. Useful after changing MCP servers or their configuration, when past measurements no longer describe the current setup. Confirm before running — the history isn't recoverable.
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.
- 8d ago First seen · 51 lines · 27 tokens per session scan A 7f1ef9fa7517
cco-tools is a skill published in the GitHub repository egorfedorov/claude-context-optimizer (107 stars, last pushed 6d ago), licensed MIT. It adds 27 tokens to every session and 419 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.
Other skills, from other repositories
alive:demo
Generate a believable, lived-in ALIVE world from a free-text persona description (custom path) or a deterministic sandbox preset. Routes the create/list/activate/deactivate/delete/status surface and orchestrates the 5-stage subagent generation pipeline.
alive:system-upgrade
Upgrade ALIVE to the current version. Handles v1/v2/v3.x source states, multi-surface aware (alive-mcp / Hermes / Codex), retroactive version detection, partial-failure resume, dry-run previews, and rollback inspection.
alive:save
The human wants to checkpoint. Or: the stash has grown heavy — 5+ items, 30+ minutes, a natural pause in the work. The squirrel doesn't decide when to save. It surfaces the need and lets the human pull the trigger. Runs the full save protocol: confirms stash, writes log, updates state, generates projections…
alive:system-cleanup
The world feels messy. Stale tasks, orphan folders, v2 remnants, unsaved sessions — entropy is accumulating and needs to be addressed before it compounds. Scans across all walnuts, then surfaces issues one at a time.
alive:create-walnut
Something new is emerging. A venture, an experiment, a person entering the orbit, a life area getting serious. It needs its own walnut — its own identity, history, and future. Scaffolds the full structure, maps existing context sources, and optionally migrates files across.
alive:session-history
Revive sessions (quick or heavy), browse, and search — 'what happened recently?', 'find the session where we discussed X', 'revive yesterday's session'. For single-session recall and multi-session browsing. If the human needs to merge multiple sessions into one working context or detect conflicts between parallel…