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/sfc-gh-dflippo/snowflake-dbt-demonpx agentmods add skills/sfc-gh-dflippo/snowflake-dbt-demo/proc-fixerWrote 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/proc-fixer)<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/proc-fixer"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/proc-fixer/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/proc-fixer"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/proc-fixer.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 | $0.00075 | $0.04145 |
| Opus 5 | $0.00037 | $0.02073 |
| Sonnet 5 | $0.00015 | $0.00829 |
| Haiku 4.5 | $0.00007 | $0.00415 |
Grade A, and why
proc-fixer 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proc Fixer (scripting flavor)
Repair a single converted mapping procedure — an Informatica mapping converted to a standalone Snowflake
Scripting stored procedure — that still contains unsupported-transform stubs (!!!RESOLVE EWI!!!). Each
materialized transformation is a block delimited by boundary markers; the fixer reconstructs each defective
block's SQL from the source transformation node it was converted from, splices it back, then deploys, CALLs,
and grades the procedure against the source-derived assertions until it creates clean and all assertions pass.
The fix is authored from source semantics, not guessed from the broken SQL, and the expected result the fix is graded against is computed by the test generator from the source — so the loop has an independent target.
Scope. This is the data-flow counterpart to orchestration-fixer (which repairs control-flow elements of a task graph) and the scripting-flavor analog of dbt-fixer (which repairs dbt models). In dbt mode a mapping becomes a model repaired by dbt-fixer; in scripting mode a mapping becomes its own stored procedure repaired here. It consumes the assertions authored by proc-test-gen — that pair owns the ARRANGE + ASSERT; this skill owns the ACT (the fix) and drives the repair loop.
Autonomous mode: When spawned as a team agent, skip all interactive stopping points, make reasonable defaults, and document assumptions in the completion report. When done,
send_messagetomainwith your results, and respond to anyshutdown_requestwithtype: "shutdown_response",approve: true.
Where this sits in the fix loop
block-locate ── the defective block + its span/body (scripts/stabilization_tools.py block-locate, marker-scoped)
ewi-extract ── the block's !!!RESOLVE EWI!!! / SSC-* defects (scripts/stabilization_tools.py ewi-extract)
proc-fixer ── [THIS SKILL] reconstruct the fixed block SQL from the source transformation node
block-replace ── splice the fix back between the markers, integrity-checked (scripts/stabilization_tools.py block-replace)
deploy-and-call ─ deploy the one proc into the test schema + CALL it (scai code deploy-and-call)
grade ── run the source-derived assertions against the populated target; PASS/FAIL feeds this loop
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.
- 2d ago First seen · 254 lines · 75 tokens per session scan A 1f95dacf881f
proc-fixer 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 75 tokens to every session and 4,145 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 2026-09-10.
Other skills, from other repositories
reproduce-bug
Reproduce a reported bug in googleapis/mcp-toolbox and decide whether it is real, delivering an evidence-backed verdict: confirmed, already fixed, misconfiguration, client-side, works as intended, not reproducible, or blocked. Use whenever a maintainer asks you to reproduce, verify, confirm, or investigate a bug…
fix-failing-tests
Diagnose a failing test in the googleapis/mcp-toolbox repo and land a fix by reasoning from the actual error: read the failure, reproduce it, shrink it until the cause is forced into the open, then fix the cause. Use this whenever a test or CI job is red, a build breaks after a change, many packages fail at once, or a…
triage-issues
Triage GitHub issues in the googleapis/mcp-toolbox repo: propose the correct labels (type / priority / product / status), check for duplicates, verify a bug has enough info to act on, and draft a triage comment. Use whenever a maintainer asks you to triage, label, categorize, prioritize, or "look at" an issue (or a…
postgresql-indexing
PostgreSQL indexing best practices for Prowler: index design, partial indexes, partitioned table indexing, EXPLAIN ANALYZE validation, concurrent operations, monitoring, and maintenance. Trigger: When creating or modifying PostgreSQL indexes, analyzing query performance with EXPLAIN, debugging slow queries, reviewing…
graphjin-eval
Create, extend, run, baseline, and diagnose GraphJin agent evaluations through the graphjin eval CLI.
axiom-audit-grdb-performance
Use when the user mentions GRDB performance review, slow GRDB queries, app-group database setup audit, a ValueObservation that stopped updating, or pre-release GRDB scan.