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 sfc-gh-dflippo/snowflake-dbt-demo --skill tag-objectsgit clone --depth 1 https://github.com/sfc-gh-dflippo/snowflake-dbt-demoWrote 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/sfc-gh-dflippo/snowflake-dbt-demo/tag-objects)<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/tag-objects"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/tag-objects/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/sfc-gh-dflippo/snowflake-dbt-demo/tag-objects"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/tag-objects.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 | $0.00054 | $0.00602 |
| Opus 5 | $0.00027 | $0.00301 |
| Sonnet 5 | $0.00011 | $0.00120 |
| Haiku 4.5 | $0.00005 | $0.00060 |
Grade A, and why
tag-objects 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 2d 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tag objects
Tags are the user's own labels on a code unit — pii, finance, needs-review. They mean nothing
to the state machine and gate nothing: no task reads them, and tagging never changes an object's
stage. They exist so a person can group objects the registry has no field for.
Tags live at extensions.tags as an array of objects:
[{ "id": "pii", "details": {} }, { "id": "finance", "details": { "owner": "ap" } }]
id is the label the app renders as a chip. details is a free-form map for anything the user
wants to carry with the tag; leave it {} when there is nothing to put in it.
Tagging
update_registry's value writes raw JSON at an extensions.<path> field. It replaces the
whole array, so read the current tags before writing:
query_registry(where="<filter>", fields="id,source,extensions")—extensionsis not in the default projection, so it must be named or the current tags come back empty and you will drop them.- Merge: add the new tag (or drop the one being removed) to the array you just read.
update_registry(field="extensions.tags", value=<the merged array>, objects="<id>")
Untagging is the same three steps with the tag removed. To clear every tag, write [].
Tag one object per call when the tag sets differ — objects="a,b" and where= write the same
array to every match, which is right for applying a shared tag to a batch and wrong for merging
into objects that already have different tags.
Finding tagged objects
The registry filter has no array-contains operator; an array compares as its JSON text, so match a
tag with LIKE:
query_registry(where="extensions.tags LIKE '%\"pii\"%'", fields="id,source,extensions")
Quote the id as it appears in the JSON ("pii", with the quotes inside the %) — a bare %pii%
also matches a tag named pii-review and any details value containing the word.
Reporting back
Say which objects you tagged and with what. Mention that tags show as chips on the object rows in the app's Objects panel, so the user can see them without asking.
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.
- 2d ago First seen · 55 lines · 0 tokens per session scan A cc9de3cc2591
tag-objects is a skill published in the GitHub repository sfc-gh-dflippo/snowflake-dbt-demo (33 stars, last pushed 3d ago), licensed Apache-2.0. It adds 54 tokens to every session and 602 once invoked, about $0.0003 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 2026-09-10.
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