agentic-resources/workplans/AGENTIC-WP-0005-detect-hardening.md

id, type, title, domain, repo, status, owner, topic_slug, created, updated, state_hub_workstream_id

id	type	title	domain	repo	status	owner	topic_slug	created	updated	state_hub_workstream_id
AGENTIC-WP-0005	workplan	Coding Session Memory — Detect Hardening (quality filter + infra signals)	helix_forge	agentic-resources	finished	codex	helix-forge	2026-06-07	2026-06-07	d8b7b8d1-1d85-4d2a-8ccd-7b0366a9442d

Coding Session Memory — Detect Hardening

A focused hardening pass (call it Phase 1.5) so the Detect output is trustworthy enough to drive an infrastructure assessment. Triggered by ad-hoc analysis of the live store after Phase 2:

• Of 72 captured sessions, only 31 are real coding sessions; the rest are health-checks / smoke-tests / interrupted runs (mostly llm-connect "Say hello in one word"). The abandoned outcome heuristic mislabels these, and Phase 2 cataloged a false-positive "cross-flavor abandoned" pattern as approved/distribution_ready.
• All 31 real sessions read as success, so the current signal set (outcome + markers + cost) surfaces almost no genuine friction.
• The already-captured tool_histogram tells the real story: ~17% of tool activity in real sessions is State Hub MCP + task plumbing + ToolSearch schema-loading, concentrated to 40–70% in some sessions — but signals.py never looks at it.

No new capture is needed — this is analysis the data already supports.

Session-Quality Filter

id: AGENTIC-WP-0005-T01
status: done
priority: high
state_hub_task_id: "9f8b4304-0a37-4f66-ad34-d93e12fba0d8"

Add detect/quality.py with is_real_coding_session(digest) that filters out health-checks, smoke-tests, interrupted, and trivially-short sessions (event-count floor, repo present, substantive edit/tool activity, not a single hello/interrupt prompt). Wire it into the detect pipeline so signals/clusters only form over real sessions — fixing the abandoned false-positive. Knobs under [detect] in config.toml. Unit-tested on synthetic trivial-vs-real digests.

Infra-Overhead + Thrash Signals

id: AGENTIC-WP-0005-T02
status: done
priority: high
state_hub_task_id: "10d57b05-a731-4ece-bf45-f6a98ac77555"

Add tool_histogram-based extractors to detect/signals.py: a shared tool-bucket helper (shell / edit / read / statehub_mcp / task_mgmt / schema_load / other); sig_infra_overhead (PROBLEM when the statehub+task+schema share of tool calls exceeds a threshold; magnitude = share; locus infra_overhead); sig_schema_thrash (ToolSearch count over threshold; locus schema_load); sig_tool_thrash (extreme single-tool repetition). Pure functions over digests; thresholds configurable. Unit-tested.

Re-run Live, Purge False Positives, Ranked Friction Report

id: AGENTIC-WP-0005-T03
status: done
priority: high
state_hub_task_id: "8b9d029a-60d0-4caf-af62-4fcc9c9a645c"

Re-run ingest → detect over the real local sessions with the filter + new signals. Purge the false-positive catalog entries seeded in Phase 2 (the health-check abandoned pattern) and re-curate so the catalog reflects real friction. Produce a ranked friction assessment (docs/ASSESSMENT-infra-friction.md) of the major infrastructure problems — quantified per repo/flavor, infra-overhead share, schema-thrash — with recommendations (incl. the State Hub / MCP skill hypothesis). After workplan file updates, notify the operator to run from ~/state-hub:

make fix-consistency REPO=agentic-resources