From 1894175f4ffbce1bf17df742436eda090f8a41fc Mon Sep 17 00:00:00 2001 From: Claude Date: Tue, 14 Jul 2026 19:43:03 +0000 Subject: [PATCH] content(blog): The tool-calling glue is coming from GitHub, not labs --- ...2026-07-14-the-tool-calling-glue-is-diy.md | 61 +++++++++++++++++++ 1 file changed, 61 insertions(+) create mode 100644 frontend/content/blog/2026-07-14-the-tool-calling-glue-is-diy.md diff --git a/frontend/content/blog/2026-07-14-the-tool-calling-glue-is-diy.md b/frontend/content/blog/2026-07-14-the-tool-calling-glue-is-diy.md new file mode 100644 index 0000000000..ee00edf0c3 --- /dev/null +++ b/frontend/content/blog/2026-07-14-the-tool-calling-glue-is-diy.md @@ -0,0 +1,61 @@ +--- +title: "The tool-calling glue is coming from GitHub, not labs" +description: "A cost-cutting Claude Code orchestrator, a geospatial SQL skill, and a Claude-Codex review loop, all built by individuals, not a model vendor's product team." +slug: the-tool-calling-glue-is-diy +topic: tool-calling +date: 2026-07-14 +articles: + - https://github.com/Nanako0129/pilotfish + - https://github.com/dekart-xyz/geosql + - https://aimaker.substack.com/p/claude-code-workflow-setup +--- + +None of this week's three most interesting tool-calling projects came out of +a model vendor's blog. All three are solo or small-team efforts stitching +Claude, Codex, and cheaper models together through skills, subagents, and +MCP — the parts of the stack Anthropic and OpenAI ship as raw primitives but +don't finish for you. + +[Pilotfish](https://github.com/Nanako0129/pilotfish) packages a pattern +Anthropic benchmarked but never shipped as a product: let Fable 5 plan and +review inside your main Claude Code session, and hand the actual execution to +cheaper Sonnet or Haiku subagents. On BrowseComp, that combination lands at +86.8% accuracy against Fable-alone's 90.8% — roughly 96% of the performance +for 46% of the cost. Pilotfish's contribution is packaging that as a handful +of fixed roles and a one-prompt installer, rather than a sprawling catalog of +agents. The catch shows up more in Anthropic's own write-up than in +pilotfish's docs: Fable's edge isn't the checklist work you can hand off, +it's noticing something's wrong when nothing on the checklist says so, and +that doesn't delegate to a cheaper model. If your Claude Code bill is the +actual problem, try it. If you're leaning on Fable for judgment calls, keep +it in the loop instead of behind one. + +[GeosQL](https://github.com/dekart-xyz/geosql) turns Claude or Codex into a +geospatial analyst that writes real PostGIS, BigQuery, and Snowflake SQL +instead of guessing table names: it explores your warehouse schema first, +dry-runs BigQuery queries against a 10 GiB cap before executing them, and +renders results on a map so the agent can catch a geometry mistake a +text-only review would miss. That map-in-the-loop step is the actual idea — +the project's own comparison shows task success far lower without it. Worth +flagging: a commenter on the project's Hacker News thread pointed out that +the eval chart and the surrounding prose don't agree, a graph showing single +digits next to text claiming success across the board. It's trending on +GitHub regardless, and the underlying idea — let the agent see its output, +not just describe it — generalizes well past geospatial data. + +[The AI Maker's write-up](https://aimaker.substack.com/p/claude-code-workflow-setup) +on wiring Codex into a Claude Code workflow is less about one tool than about +where MCP is actually landing a year in: as the connector to a handful of +external systems, with skills doing the cheap, repeatable orchestration +around them. A community project, ching-kuo's claude-codex, shows the shape +concretely — Codex reviews Claude's diffs over MCP and hands back only a +structured verdict, capped at three fix-and-recheck rounds, specifically so +a second opinion doesn't cost more than the bug it catches. Small pattern, +but it's the same one running through all three stories: nobody's waiting +for Anthropic or OpenAI to ship the glue between their own tools, so people +are writing it themselves in skills and thin MCP wrappers. + +Of the three, pilotfish is the one I'd actually install — the cost math +holds up, and it doesn't ask me to trust a chart that contradicts its own +text. GeoSQL's map-in-the-loop trick is the one I'd steal for something +outside geospatial work, once someone reconciles those numbers.