docs: snapshot of the project's Claude Code memory

Decisions, environment quirks and pitfalls learned while working on AgentHub
(docs/claude-memory/, indexed by MEMORY.md). Notes holding personal account
details are left out.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

docs/claude-memory/claude-haiku-5-5.md

@@ -0,0 +1,23 @@
+---
+name: claude-haiku-5-5
+description: "Claude Haiku 5.5 (2026-10-07) facts + its 100k-token price tier, which AgentHub's pricing does not model"
+metadata:
+  node_type: memory
+  type: reference
+  originSessionId: f2f2cbeb-6ac1-4876-8b8a-f8dc6cd3a17b
+  modified: 2026-10-08T03:58:14.256Z
+---
+
+Source: https://www.anthropic.com/claude-haiku-5-5 (read 2026-10-08).
+
+- Model id `claude-haiku-5-5`, released 2026-10-07. Cheapest/fastest small model; first Haiku with effort levels (low/med/high/xhigh/max); computer/browser use in beta; new tokenizer uses slightly more tokens per task.
+- Per MTok, split at a **100k-token prompt**: input $0.10/$0.50, output $0.50/$2.50, cache write $0.125/$0.625, cache read $0.01/$0.05. (Haiku 4.5: $1/$5/$1.25/$0.10, flat.)
+- Same day: **Sonnet 5.5 cache read was halved, $0.20 → $0.10** (input $2, output $10 unchanged).
+- Anthropic positions it for summaries, compaction, classification, subagents; Sonnet/Opus 5.5 still better for complex agentic coding (Terminal-Bench 4.0: 39.2% vs Sonnet 70.6%).
+- Platforms: Claude API, AWS, Google Cloud, Azure.
+
+AgentHub status 2026-10-08: the >100k tier is now modelled (uncommitted), as SUBSET columns `long_*_tokens` on token_usage/token_usage_hourly plus `model_pricing.long_input_per_mtok`/`long_output_per_mtok`, synced from LiteLLM's `*_above_100k_tokens`. It was deliberately NOT done as a new primary-key dimension: prod (4820) and dev (4830) share one DB, so a PK rebuild would break the older build's `ON CONFLICT`, and splitting rows would double-count under the high-water-mark baselines. Threshold is the single `LONG_CONTEXT_TOKENS` = 100k.
+
+Useful for the user's own work:
+- A good cheap model for subagents doing exploration, summaries or classification. AgentHub's AI commit message (`server/lib/commit-message.js`, `--model haiku` alias) now gets it automatically and costs about 10× less. Nothing needs to change.
+- Its cyber safeguards still BLOCK pentest/attacker techniques, so it is the wrong model for Strix pentest work. Use Sonnet/Opus there.