v0.10.0 - learn-by-example depth + agent discovery

v0.10.0

Find it by example, and let agents find it at all. A worked example for every framework, a cross-library Showcase that hands off to pm-skills, the agent-discovery index switched on, and the behavioral-eval numbers refreshed across the full 56-skill catalog. No new frameworks; the catalog stays 56.

For everyone

• A quick worked example for every framework. The new Samples shelf gives each of the 56 skills one compact, end-to-end example - a real situation, the prompt, and the full artifact - so you can scan the whole library by example. Example coverage is now 56 of 56.
• A cross-library Showcase: tfs decides, pm-skills delivers. Three companies (Storevine, Brainshelf, Workbench) each take one feature from a raw decision to a launch call, then hand the reasoning artifact off to the matching pm-skills delivery artifact - so you can follow one company across both libraries. See the "Browse by company" section of the Showcase.
• The trust page is current. Both behavioral evals were re-run across all 56 skills (routing: 99% top-1, 0 false-fires across 673 cases; artifact quality: 99% of 389 checks, 53 of 56 skills perfect), and the Does this actually work? page now reflects the full catalog, not the earlier 47-skill run.

For builders

• The agent-discovery index is switched on. v0.9.0 published a machine-readable catalog; this release makes it discoverable - llms.txt is now linked from robots.txt and every page, and a new llms-full.txt inlines the whole catalog (every component plus the 79 not-shipped methods) so an agent can ingest it in one fetch.
• red-team-light re-graded P -> M (transferred). Its core move - construct the strongest contrary case - is the well-studied "consider the opposite" debiasing technique (Lord, Lepper & Preston 1984; Mussweiler et al. 2000; Hirt & Markman 1995), so its grade rises a notch, with the honest caveats kept: group-dissent research does not transfer, and the evidence is human-subject, not AI-validated.