Three coordinated changes that let the pipeline produce a clean
chapter-by-chapter git history on long texts without archaeology after
the fact.
1. Richer commit messages. `SourcePipeline._git_commit` now diffs the
staged changes, buckets added files by output subdirectory (entities,
evaluations, classifications, mappings, analyses, metrics, logs), and
includes counts in the commit body. So `git log` reads "entities:
+23, evaluations: +23" per chapter instead of the same generic blurb
on every commit. Zero behaviour change when no output changed; falls
back to the original message if the diff query fails.
2. --eval-after-source / --classify-after-source on `infospace process`.
After a source's stages succeed, the pipeline identifies which entity
files are *new* (set diff of entity slugs before vs after), loads
their EntityMeta, and runs per-entity evaluation and/or
classification scoped to just those slugs before the per-source git
commit lands. Result: each chapter's commit is self-contained —
extraction + evaluation + classification in one atomic unit. Gated
behind explicit flags because the cost is real (LLM latency per
chapter rather than amortised across one bulk batch).
3. `markitect infospace chapters` subcommand. Lists source files in
canonical order with entity count, evaluated count, classified
count, and mean per-entity score per source. Text or JSON output.
Natural triage surface for long-text infospaces — spot chapters that
under-extracted or evaluated poorly.
Also: `docs/advanced-usage.md` gets a new "Systematic processing of
long texts" section with the recommended flag combo and the tradeoff
note on cost.
11 new unit tests cover the chapters command (text/json/no-sources),
the process flag wiring (help + provider requirement), and the
commit-body bucket logic. Full infospace+llm unit suite (315 tests)
green; 3 pre-existing infospace failures unchanged.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Five improvements that eliminate most of the agent-in-the-loop friction
observed while closing out the 988-entity WoN evaluation (C.1):
1. Gemini adapter now retries on 429 + 5xx with exponential backoff
(same pattern already used by OpenRouter/OpenAI). Removes the need
for shell-level retry wrappers when hitting free-tier rate limits.
2. evaluate CLI prints the underlying error ("ERROR — HTTP 503 …")
instead of a bare "ERROR", so agents don't have to drop into Python
to diagnose transient failures.
3. --entity/--chapter now respect existing evaluation files by default
(previously only the full-collection pass did). New --force flag
opts into re-evaluation. Stops silently burning free-tier quota on
re-runs of the same slug.
4. --entity accepts hyphenated slugs (matching entity filenames) and
normalizes them to the underscore form used on disk. On a miss the
CLI suggests near matches instead of a bare "not found".
5. eval-summary --update-metrics is no longer destructive:
read_metrics_file/write_metrics_file preserve structured values
(type_distribution) and don't flatten ints to floats. Fixes a
silent data loss observed on every run.
Bonus: the evaluator field in written evaluation frontmatter now
falls back from run_config.model_name to the adapter's resolved model
(or the model echoed back in the API response), so rows no longer
show `evaluator: null` when --model is omitted.
Tests: new tests/unit/llm/test_gemini.py covers retry behavior;
tests/unit/infospace/test_history.py gains a round-trip test that
pins the type_distribution / int-preservation invariants.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
History module with snapshot creation from check results, metrics file
I/O, auto-append to history after checks, date-based snapshot lookup,
and metric trend extraction. CLI commands: history, history-diff.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Evaluation pipeline builds prompts from entity metadata, delegates
to BatchEvaluator, parses structured LLM responses into ScoreEntry
objects, and writes evaluation files. CLI: 'markitect infospace evaluate'
with --provider, --entity, --chapter filters.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Adds 'markitect infospace' command group with init (create config),
status (entity count/domains/disciplines), entities (list with sort),
and viability (threshold dashboard with pass/fail).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
InfospaceConfig (topic, disciplines, schemas, competency questions,
viability thresholds, pipeline) with YAML load/save and directory
discovery. InfospaceState aggregates entities, evaluations, and
viability checks for status reporting.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add data models (ScoreEntry, EntityEvaluation, EvaluationSnapshot,
SnapshotDiff) and I/O utilities for YAML frontmatter evaluation files,
snapshot persistence, history append, and snapshot diffing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Deterministic validation of EntityMeta against declarative schemas:
section presence/word counts, heading format, domain enum values.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Extract section-tree algorithm from SchemaGenerator into standalone
core/section_tree.py and build markitect/infospace/ package with
EntityMeta dataclass and parse_entity_file/parse_entity_directory.
Foundation for schema compliance, coverage, and granularity metrics.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
