Commit graph

4 commits

Author SHA1 Message Date
e17134ee9b refactor(linkedin-studio): S31c descriptive-%-scrub — platform-norm percentages asserted as fact -> SSOT
24 edits / 12 files (+26/-26). Unsourced platform/algorithm/audience percentages reconciled to
SSOT vocabulary (figure/proportion/multiplier unverified). Catalog + new sibling clusters
(64% follow-up x5, wrong-window 70% x4, Stage-2 6-10% x2) + borderlines (70% retention, 70%
mobile) + the ~3% save-worthy straggler (surfaced, not silent). The SSOT-sourced ~70% reach
figure is KEPT; only the wrong window corrected (60min/1h -> first 15-30 min). Sourced/computed
benchmarks kept (Buffer 178%/247%, Socialinsider 11%). KEPT C1: ~45% AI-comment figure (already
hedged correlational/medium-confidence). Gate 81/0/0 exit 0, counts 29/19/26 + v0.5.0.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016qgzo6rxthw7KuxHjn5vyE
2026-06-20 09:54:44 +02:00
2b9ed1cf0b fix(linkedin-studio): S27 ref-consistency A — "penalty/penalizes" framing → SSOT
Reconcile external-link and topic-relevance reach-loss framing to the algorithm-signals
SSOT across 6 files (10 edits): body links "correlate with lower reach" (LinkedIn denies
an intentional penalty), topic relevance is a positive ranking input with no quantified
off-topic figure. 3 plan-cited lines + 7 same-class siblings surfaced during verify.

Bucket B (link-penalty lines in linkedin-formats.md) folded into S28; Bucket D (other
unsourced reach-coefficients: -68%/-25%/-15-25%/-30-50%/55%) queued as new S30. Engagement-
pod + AI-slop "penalized" framing left intact (officially confirmed). Gate 81/0/0; counts
29/19 unchanged.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016qgzo6rxthw7KuxHjn5vyE
2026-06-19 22:06:39 +02:00
3dd8f40c31 fix(linkedin-studio): propagate reconciled algorithm numbers, cite-not-restate
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-05-29 20:32:17 +02:00
Kjell Tore Guttormsen
40986575b6 feat(ultraplan-local): v1.6.0 — /ultraresearch-local deep research command
Add /ultraresearch-local for structured research combining local codebase
analysis with external knowledge via parallel agent swarms. Produces research
briefs with triangulation, confidence ratings, and source quality assessment.

New command: /ultraresearch-local with modes --quick, --local, --external, --fg.
New agents: research-orchestrator (opus), docs-researcher, community-researcher,
security-researcher, contrarian-researcher, gemini-bridge (all sonnet).
New template: research-brief-template.md.

Integration: --research flag in /ultraplan-local accepts pre-built research
briefs (up to 3), enriches the interview and exploration phases. Planning
orchestrator cross-references brief findings during synthesis.

Design principle: Context Engineering — right information to right agent at
right time. Research briefs are structured artifacts in the pipeline:
ultraresearch → brief → ultraplan --research → plan → ultraexecute.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-08 08:58:35 +02:00