A Claude skills playbook for debugging why a skill never fires, fires wrong, or fails
socialwithaayan · x · 2026-07-24
This post frames Claude skills as a debugging problem. The author says many skills fail not because the implementation is wrong, but because the description never routes the request correctly.
They propose diagnosing failures across a few classes such as:
- Never fired: the skill never loaded, usually because the description is too vague or another skill captured the request first.
- Fired wrong: the skill loaded on the wrong request.
- Fired but failed: the skill triggered, but the body or implementation broke later.
The practical point is that skill libraries need structured failure analysis, not just more instructions.
More from coding & agent
- Goal-driven AI needs verifiable success signals, or it invents its own — daniel_mac8 · 2026-09-11
- Frontier models need ways to verify success — or they'll invent their own — daniel_mac8 · 2026-09-11
- Sakana AI launches Fugu Max: dynamic multi-agent routing across its largest open-model pool — graceisford · 2026-09-11
- Is inference latency becoming the biggest bottleneck for production AI agents? — Euphoric_Sea632 · 2026-09-11
- Anthropic researcher: 99% of engineers now run swarms of 300+ self-improving agents — AlishaOutridge · 2026-09-11
- Gergely Orosz: Shipping 10x PRs With AI Agents, Sites Fill With Small Regressions — ducha_aiki · 2026-09-11