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 collibra/chip --skill indexgit clone --depth 1 https://github.com/collibra/chipWrote 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/collibra/chip/index)<a href="https://agentmods.dev/skills/collibra/chip/index"><img src="https://agentmods.dev/badge/skills/collibra/chip/index/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/collibra/chip/index"><img src="https://agentmods.dev/badge/skills/collibra/chip/index.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00017 | $0.00962 |
| Opus 5.5 | $0.00007 | $0.00385 |
| Sonnet 5.5 | $0.00003 | $0.00192 |
| Haiku 4.5 | $0.00002 | $0.00096 |
Grade A, and why
index 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.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Collibra skills — navigator
This MCP server is a bridge to Collibra Data Governance Center. Skills under
collibra/* document the non-trivial workflows: when tools must be chained, when one ID space
must be bridged to another, and which permissions are required.
When to load which skill
| Task | Skill |
|---|---|
| Find data about a topic by meaning (semantic) vs by exact name (keyword) | collibra/discovery |
| Trace upstream sources, downstream consumers, or impact of a change | collibra/lineage |
| Create any new asset (Business Term, Table, Column, KPI, …) | collibra/asset-create |
| Modify an existing asset's attributes, relations, tags, status, or owners | collibra/asset-edit |
| Register a table (and its dimension tables) as a Collibra Data Product with ports | collibra/data-product-create |
| Generate governed YAML context (semantic blueprints, metric definitions) for an asset | collibra/context |
Data quality skills are not listed here: the data quality tools are a capability this server
may be run without, and their skills are only served when it is switched on. When they are
served, list_collibra_skills lists them — search it for "data quality" before assuming a DQ
workflow has no guide.
If a task is a single tool call with no chaining (e.g. get_asset_details by UUID,
list_asset_types, pull_data_contract_manifest), no skill is needed — the tool's own
description is sufficient.
Where to get each id / publicId
create_asset and edit_asset accept types by UUID, publicId, or display name. When you need
the authoritative UUID or publicId for a type, fetch it from:
| Concept | Tool | Field |
|---|---|---|
| Asset type id / publicId | list_asset_types |
id / publicId |
| Attribute type id / publicId | prepare_create_asset |
attributeSchema[].attributeTypeId / attributeSchema[].publicId |
| Relation type id / publicId | prepare_create_asset |
relationTypes[].relationTypeId / relationTypes[].publicId |
get_asset_details returns attribute and relation display names only (via
assignableAttributes[].name and the relation lists) — use prepare_create_asset to resolve
those names to a type id or publicId.
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 Changed · +3 lines 315235732939
- 2mo ago First seen · 69 lines · 17 tokens per session scan A 4270c57e0611
index is a skill published in the GitHub repository collibra/chip (37 stars, last pushed yesterday), licensed Apache-2.0. It adds 17 tokens to every session and 962 once invoked, about $0.0001 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 2026-08-30.
index compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| indexcollibra/chip | Skill | 37 | yesterday | Apache-2.0 | A | 17 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |