Agent of the Day – September 14, 2026
Every AI-heavy codebase has the same quiet failure mode: a provider ships a new flagship model, nobody updates the alias map, and workflows silently fall back to a stale default until someone notices the bill or the benchmark looks off. Today’s Agent of the Day exists specifically to close that gap before it opens — the Daily Model Inventory Checker .
Agent of the Day: Daily Model Inventory Checker
Section titled “Agent of the Day: Daily Model Inventory Checker”This scheduled gh-aw workflow (.github/workflows/daily-model-inventory.md) runs once a day and treats model tracking like a real audit, not a scrape-and-hope job. It pulls live catalogs from OpenAI, Anthropic, and Google directly via their APIs, uses the built-in AWF /reflect endpoint to query Copilot’s own model metadata, and cross-references everything against pkg/workflow/data/model_aliases.json and pkg/cli/data/models.json — the two files that decide which model a workflow actually gets when it asks for large or agent.
Its last three scheduled runs — Sept 11, Sept 12, and Sept 13 — all completed cleanly, with zero errors and zero warnings across the board, spending 13 to 18 minutes and 35k–75k tokens per run to reconcile roughly 240 models across five providers each time.
The workflow’s real value shows up when it finds something. On September 9, it surfaced issue #59709, “Model alias inventory update - 2026-09-09,” reporting that OpenAI’s new flagship gpt-6-astra was live in both the Copilot and OpenAI catalogs but wasn’t covered by any existing alias glob — meaning workflows requesting large or agent would silently miss the newest, most capable model. The issue laid out exact pricing ($1,000 / $5,000 per million tokens, input/output), the precise alias diff needed, and a full breakdown of all 242 models it had checked across every provider, including which legacy IDs to deliberately leave alone.
That report turned directly into two merged pull requests: #59711, which added the gpt-6 alias pattern and wired gpt-6-astra into the large and agent resolution chains along with its pricing metadata, and #59703, a same-day fix bumping the Copilot SDK dependency after a version mismatch had briefly broken the inventory job itself. Both merged within roughly 15 minutes of being opened.
What stands out about this agent isn’t volume — it’s precision and restraint. Its own report explicitly calls out that no other alias gaps existed that day, walks through why each existing wildcard (gemini-*flash*, gpt-5.x, sonnet/opus/haiku) still correctly catches every other new model observed, and preserves historical entries like claude-opus-4.5 and gpt-4.1 rather than pruning them, in case older workflows still reference them. It also cross-validates pricing from two independent sources — Copilot SDK billing data and the reflect endpoint — and only proposes a change when both agree. When nothing needs fixing, it stays quiet; when something does, it hands maintainers a fully-sourced diff instead of a vague nudge.
For a project that runs hundreds of AI-driven workflows depending on consistent model resolution, that kind of nightly discipline is the difference between a broken default nobody notices for weeks and a same-day, two-PR fix.
Curious how workflows like this one are built? Check out github/gh-aw and see what your next agent could catch.