/log-evidence

name: log-evidence
description: "Record findings from completed offline human tasks (interviews, observations, outreach) back into the canvas. The re-entry point after /mycelium:handoff."
metadata:
  instruction_budget: "58"
  framework_dependency: "mycelium"
  framework_dependency_note: "This skill is designed to run within the Mycelium framework (https://github.com/haabe/mycelium). Standalone use will skip the canvas state, theory gates, and harness behavior the skill assumes. Install: /plugin install mycelium@haabe-mycelium."

Log Evidence Skill

The re-entry point after offline human work. Takes raw conversation notes, observations, or survey results and integrates them into the canvas with proper provenance.

Preflight: Read target canvas file(s) before any Write/Edit

**Hard rule.** Before issuing `Write` or `Edit` against any `.claude/canvas/*.yml`, use the **Read tool** on that file in this session. Claude Code's Read-before-Write check requires the `Read` tool specifically — `cat`/`head`/`grep` via Bash do NOT satisfy it.

**Edit vs Write — different cost profiles** (verified 2026-05-14):

• **`Edit`** (exact-string replacement): `Read` with `limit: 1` satisfies the check at ~50 tokens. State-tracking is per-file, not per-byte — subsequent `Edit` calls work anywhere in the file. Use this for partial updates against large canvas files (e.g., `purpose.yml` at 800+ lines).
• **`Write`** (full replacement): do a **full Read** first. Write obliterates the file; you should see what you're about to replace. The `limit:1` shortcut is *not* appropriate here.

**ID-bearing entries — scan the ID space before assigning** (added 2026-05-15, v0.23.19): When adding a new component, opportunity, solution, or any other ID-bearing entry to a canvas file, run a Bash grep first to confirm the next ID in your prefix sequence is actually free:

grep -o "<prefix>-[0-9][0-9]*" .claude/canvas/<file>.yml | sort -u -t- -k2 -n | tail -3

Replace `<prefix>` with the canvas's ID prefix (`comp` for landscape, `opp` for opportunities, `sol` for solutions, `ht` for human-tasks, etc.). Then pick the next free integer, **matching the zero-padding already used in that file**. The sort is NUMERIC (`-t- -k2 -n`) rather than lexical, and that is not pedantry: a plain `sort -u` orders `ht-1` after `ht-080`, so on a canvas with inconsistent padding it reports the wrong maximum and the next ID collides. Verified on the dogfood repo 2026-08-13, where lexical sort returned `ht-1` as the highest human-task ID against an actual `ht-080`. `grep -o` is also deliberate: it matches IDs wherever they appear, including cross-references and prose, so an ID that was promised somewhere but not yet defined is not handed out twice. `validate_canvas.py` has a duplicate-ID check (lines 230-239) that catches the failure on CI, but a duplicate can persist in the working tree for days if CI isn't run between edit and discovery — see roadmap-repo `corrections.md` 2026-05-15 "Duplicate canvas ID created in landscape.yml" for the worked example.

Original failure mode: anti-pattern #7 instance #5, 2026-05-09 — agent conflated Bash `head` with the Read tool, lost ~14k tokens to a Write-fail → remedial-full-Read → re-Write loop. The `limit:1` discipline (graduated 2026-05-14, v0.23.18) prevents the second-order cost where the agent *correctly* follows the rule but full-Reads every time. The ID-scan discipline (graduated 2026-05-15, v0.23.19) prevents the related class where the agent reads enough of the file to satisfy the Edit check but not enough to see existing ID assignments — kin to anti-pattern #8 (Stale State Read).

If this skill writes to multiple canvas files, register each one first (limit:1 for Edit-only paths; full Read for Write paths) AND ID-scan any prefix you intend to assign.

See `CLAUDE.md` *Canvas writes — Read before Write* for the canonical rule.

When to Use

• After completing a human task from `.claude/canvas/human-tasks.yml`
• When the user returns from an offline conversation and has findings to record
• When SessionStart reminds about pending human tasks and the user has completed them
• When the user pastes conversation notes or interview summaries

Workflow

1. **Check pending tasks — and handle the no-matching-task case explicitly**:

• Read `.claude/canvas/human-tasks.yml` for `pending_tasks` AND `completed_tasks` — evidence frequently attaches to a task that has already closed; see the completed-task branch below
• List them: "You have [N] pending human task(s): [objective summaries]"
• Ask: "Which task did you complete? Or paste your notes and I'll match them."
• **BEFORE the no-matching-task branch: search `completed_tasks` too (added 2026-08-31).** Evidence very often arrives days after the conversation that produced it — a name recalled later, a fact that only became relevant once something else landed. If a COMPLETED task is the one that produced this evidence, **that is where it belongs**, and neither path below fits:
• **Append a dated sub-entry to the completed task.** Do NOT reopen it, and do NOT create a new `ht`.
• **Why not reopen:** the task did complete; reopening it misreports the funnel, and every downstream count (status checks, cadence, reply-owed) then reads a closed conversation as live work.
• **Why not backfill a new task:** a late recall about a finished conversation is not a new channel. A second `ht` for one exchange splits its `touch_log` across two records, which is the failure `8c(b)` exists to prevent, arriving from the other direction.
• Say which completed task you are appending to and on what date, so the append is auditable rather than silent. Then proceed to step 2 with that `ht`-ID.
• Reported by a plugin consumer 2026-08-31 across six `log-evidence` runs: this was done correctly by improvisation every time, and was nowhere written down. Step 5's framing (*"writing evidence and closing the task are one action"*) doe