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 idescat/mcp --skill workflowgit clone --depth 1 https://github.com/idescat/mcpWrote 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/idescat/mcp/workflow)<a href="https://agentmods.dev/skills/idescat/mcp/workflow"><img src="https://agentmods.dev/badge/skills/idescat/mcp/workflow/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/idescat/mcp/workflow"><img src="https://agentmods.dev/badge/skills/idescat/mcp/workflow.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 | $0.00083 | $0.01228 |
| Opus 5 | $0.00042 | $0.00614 |
| Sonnet 5 | $0.00017 | $0.00246 |
| Haiku 4.5 | $0.00008 | $0.00123 |
Grade A, and why
workflow 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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Idescat data workflow
How to query the official statistics of Catalonia (Idescat) reliably. It
applies both to the Idescat MCP server (https://api.idescat.cat/mcp)
and to the Idescat Tables REST API
(https://api.idescat.cat/taules/v2, OpenAPI description at
https://www.idescat.cat/dev/api/taules/openapi.json). Responses follow
the JSON-stat format (see the companion jsonstat skill for how to read
them).
1. Choosing a statistic
Always start by listing the available statistics (MCP tool
get_idescat_stats; API GET /taules/v2). For each statistic, check two
key fields before choosing:
datasets(boolean): iftruethe statistic is normalized and you can drill down to tables and data. Iffalse, only the general information about the statistic is available.geo(array): available territorial breakdown levels (cat= Catalonia,prov= provinces,at= territorial plan areas,com= comarques and Aran,mun= municipalities,dis= districts,sec= census tracts). ALWAYS checkgeobefore choosing a statistic for a territorial query: if comarca-level data is requested, pick a statistic whosegeoincludescom.
Population figures
When population data is requested there are several sources: the main and richest one is CENSPH (population and housing census, annual); for half-yearly estimates there is EP (population estimates, half-yearly); and there is also PMH (municipal population register, annual). By default use CENSPH (or EP for half-yearly data). NEVER use the PMH statistic for population data unless the user explicitly asks for it.
2. Data-retrieval flow
- When specific data from a table is needed, fetch the table METADATA
first (MCP
get_table_metadata; APIGET /taules/v2/{statistics}/{node}/{table}/{geo}). If the question is about a specific territory, pass the propergeo(e.g.com,mun,prov); if you don't know the territorial divisions available, list them first (MCPget_table_geo; APIGET /taules/v2/{statistics}/{node}/{table}). Remember that without a territorial breakdown the response is the Catalonia total (cat), which does NOT include comarques, municipalities or provinces. - Check the metadata
sizefield: multiply all its elements. If the product exceeds 20,000, do not fetch the whole table (the API rejects it with HTTP 416); filter first, or tell the user and offer the HTML link to the table. - Fetch the data (MCP
get_table_dataorrender_table; APIGET /taules/v2/{statistics}/{node}/{table}/{geo}/data) with optional filters:- For a SINGLE territory or a subset, filter on the territorial
dimension (e.g.
geo=comand filterCOM=21), and/or limit the time periods with_LAST_(e.g._LAST_=2for the last two periods). - Dimension filters are query parameters named after the dimension
identifiers shown in the metadata, with comma-separated category
codes as values (e.g.
?SEX=F&COM=01,TOTAL). - When you need the full dataset (≤ 20,000 cells), fetch it without filters.
- For a SINGLE territory or a subset, filter on the territorial
dimension (e.g.
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 · 95 lines · 83 tokens per session scan A d42b7953cb8b
workflow is a skill published in the GitHub repository idescat/mcp (0 stars, last pushed 3d ago), licensed MIT. It adds 83 tokens to every session and 1,228 once invoked, about $0.0004 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 2026-09-04.
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