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 skills/beeltec/context-usage-mcp/implementnpx skills add beeltec/context-usage-mcp --skill implementgit clone --depth 1 https://github.com/beeltec/context-usage-mcpWhat 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 | $0.00043 | $0.00309 |
| Opus 5 | $0.00022 | $0.00154 |
| Sonnet 5 | $0.00009 | $0.00062 |
| Haiku 4.5 | $0.00004 | $0.00031 |
Grade A, and why
implement 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 yesterday.
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
Implement the work described by the user.
If we are not yet on a work branch create it using Conventional Branch Specification but never use AI Agent Source Prefixes.
After each subtask is done, mark it as done in the task document and do a conventional git commit with optional scope.
Check the wiki regularly for guidance and documentation on used technologies.
If the wiki has no data on the used technologies, use context7 and web search before using a technology to retrieve the latest documenation, best practices and recommendations on it. Update the wiki with this info.
Run typechecking regularly, single test files regularly, and the full test suite once at the end.
Do not overengineer. Also always ask yourself if you can implement something more ellegantly with less code.
When a task is done (and only a task, not a subtask) use /code-review to review the work.
If available, check the context length of the current session with claude-context-length-mcp after each task is done. If the sessions is greater than 150000 tokens, use /handoff
When all tasks are done and green, merge the branch with a merge commit, checkout the primary branch and delete the work branch locally
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 25 lines · 43 tokens per session scan A 3c89203839ab
implement is a skill published in the GitHub repository beeltec/context-usage-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 309 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
verify-mcp-server
Resolve and check MCP servers using MCPLookup's public identity and trust evidence. Use before recommending, installing, or connecting an MCP server; when identifying an official or first-party server; when comparing similarly named servers, packages, repositories, or endpoints; or when a user asks whether an MCP…
design-mcp-server
Design the tool surface, resources, and service layer for a new MCP server. Use when starting a new server, planning a major feature expansion, or when the user describes a domain/API they want to expose via MCP. Produces a design doc at docs/design.md that drives implementation.
add-tool
Scaffold a new MCP tool definition. Use when the user asks to add a tool, create a new tool, or implement a new capability for the server.
api-linter
MCP definition linter rules reference. Use when bun run lint:mcp or bun run devcheck reports a lint error or warning (format-parity, schema-is-object, name-format, server-json-, etc.) and you need to understand the rule, its severity, and how to fix it. Every rule ID the linter emits has an entry in this doc.
api-context
Canonical reference for the unified Context object passed to every tool and resource handler in @cyanheads/mcp-ts-core. Covers the full interface, its RequestContext base, all sub-APIs (ctx.log, ctx.state, ctx.requestInput, ctx.inputs, ctx.enrich, ctx.content), and when to use each.
api-canvas
DataCanvas primitive reference — a Tier 3 SQL/analytical workspace for tabular MCP servers, backed by DuckDB. Use when registering tables from upstream APIs, running ad-hoc SQL across them, and exporting results. Covers the acquire → register → query → export flow, per-table TTL, the token-sharing pattern for…