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/log-evidence

Record findings from completed offline human tasks (interviews, observations, outreach) back into the canvas. The re-entry point after /mycelium:handoff.

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mycelium
5263 skills

Claude Code

$ npx -y skills add haabe/mycelium --skill log-evidence --agent claude-code

SKILL.md

log-evidence.SKILL.md
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 per-file duplicate-ID check (it reports `duplicate id '<id>'`) 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; that happened on 2026-05-15, when a duplicate ID was created in `landscape.yml`.

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_PLUGIN_ROOT}/engine/agent-operating-contract.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
Read more
@haabe
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Mycelium won't make your idea good. It keeps you and your agent honest about whether it is, from first idea to market. Built on Claude Code, where the gates are structural. The files and skills port to opencode, Codex and Cursor. Outcome over output.

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Questions about log-evidence.

Which coding agents can use log-evidence?
log-evidence installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.