Modernise and re-home PyAuto workflow skills for PyAutoBrain - #5

…t on

PyAutoMind REFERENCE.md states the contract: Intake persists Difficulty: from
the shared sizing faculty "so the value shown up front is the one the Feature
Agent later acts on". It was not acted on. _feature.py mentioned Difficulty
once, where it PRINTED its own re-derived score, and read no header key at all
— not Difficulty:, not Status:, not Priority:, not Blocked-by:/Closes-when:.

The visible failure: `feature select` recommended a prompt declaring
Status: blocked, Priority: low AND an explicit Blocked-by: gate whose body says
"do not start before the queue runner has run cleanly".

Parsing lands in the sizing faculty, beside the derivation it overrides, so
declared and derived stay in one place and the bug/refactor conductors get the
same reading for free:

- declared_header() reads Difficulty/Status/Priority/Blocked-by/Closes-when,
  skipping fenced blocks. That skip is load-bearing, not tidiness: the bug
  prompt driving this fix QUOTES the offending header in a ```-block, so
  without it the bug report would declare itself blocked. Same rule and same
  reason as PyAutoMind lifecycle.py:draft_gate_refs.
- trailing `# note` comments are stripped, splitting on " #" so a Repo#123 ref
  survives intact (the live backlog has both forms on one line).
- an unrecognised Difficulty: value is ignored rather than trusted.

The ranker then honours them: declared difficulty overrides derived (with the
disagreement REPORTED, not silently resolved — the gap is evidence about the
heuristic); Priority: orders the shortlist above the difficulty term; and a
prompt declaring Status: blocked or an unresolved Blocked-by: sinks below
everything and can never be the recommended pick. It stays listed in its own
labelled band so a human can see and override, and next_action says do not
start.

declared_blocked() is deliberately conservative: this agent is offline and
cannot tell whether a gate has since closed, so an unresolved Blocked-by: reads
as blocked and the output points at `lifecycle.py issues --drafts`, which does
resolve refs against GitHub. Being wrongly held back is cheap and visible;
being wrongly recommended is the failure this exists to stop.

Measured on the live backlog: the blocked prompt drops from rank 1 to last of
27, correctly labelled, and two further blocked prompts surface that had not
been noticed by hand. draft_staleness_detection_signals moves from too-large
#26 to medium #5 — it derived too-large purely on file length, and length is a
bad size proxy because a prompt grows as it accumulates findings.

New tests are hermetic and pin the regression by the offending prompt's HEADER
SHAPE rather than the live file, so fixing the backlog cannot silently retire
them. Verified they actually bite: reverting only _feature.py fails 7 of the
10. Fixtures use invented repo names, so the file adds no tenant-firewall
instance facts.

Prompt: PyAutoMind draft/bug/pyautobrain/feature_ranker_ignores_header_keys.md

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WSCA1h6cSKMNwFmWEsxuCL

…t on (#217)

PyAutoMind REFERENCE.md states the contract: Intake persists Difficulty: from
the shared sizing faculty "so the value shown up front is the one the Feature
Agent later acts on". It was not acted on. _feature.py mentioned Difficulty
once, where it PRINTED its own re-derived score, and read no header key at all
— not Difficulty:, not Status:, not Priority:, not Blocked-by:/Closes-when:.

The visible failure: `feature select` recommended a prompt declaring
Status: blocked, Priority: low AND an explicit Blocked-by: gate whose body says
"do not start before the queue runner has run cleanly".

Parsing lands in the sizing faculty, beside the derivation it overrides, so
declared and derived stay in one place and the bug/refactor conductors get the
same reading for free:

- declared_header() reads Difficulty/Status/Priority/Blocked-by/Closes-when,
  skipping fenced blocks. That skip is load-bearing, not tidiness: the bug
  prompt driving this fix QUOTES the offending header in a ```-block, so
  without it the bug report would declare itself blocked. Same rule and same
  reason as PyAutoMind lifecycle.py:draft_gate_refs.
- trailing `# note` comments are stripped, splitting on " #" so a Repo#123 ref
  survives intact (the live backlog has both forms on one line).
- an unrecognised Difficulty: value is ignored rather than trusted.

The ranker then honours them: declared difficulty overrides derived (with the
disagreement REPORTED, not silently resolved — the gap is evidence about the
heuristic); Priority: orders the shortlist above the difficulty term; and a
prompt declaring Status: blocked or an unresolved Blocked-by: sinks below
everything and can never be the recommended pick. It stays listed in its own
labelled band so a human can see and override, and next_action says do not
start.

declared_blocked() is deliberately conservative: this agent is offline and
cannot tell whether a gate has since closed, so an unresolved Blocked-by: reads
as blocked and the output points at `lifecycle.py issues --drafts`, which does
resolve refs against GitHub. Being wrongly held back is cheap and visible;
being wrongly recommended is the failure this exists to stop.

Measured on the live backlog: the blocked prompt drops from rank 1 to last of
27, correctly labelled, and two further blocked prompts surface that had not
been noticed by hand. draft_staleness_detection_signals moves from too-large
#26 to medium #5 — it derived too-large purely on file length, and length is a
bad size proxy because a prompt grows as it accumulates findings.

New tests are hermetic and pin the regression by the offending prompt's HEADER
SHAPE rather than the live file, so fixing the backlog cannot silently retire
them. Verified they actually bite: reverting only _feature.py fails 7 of the
10. Fixtures use invented repo names, so the file adds no tenant-firewall
instance facts.

Prompt: PyAutoMind draft/bug/pyautobrain/feature_ranker_ignores_header_keys.md


Claude-Session: https://claude.ai/code/session_01WSCA1h6cSKMNwFmWEsxuCL

Co-authored-by: Claude <noreply@anthropic.com>