ktg-plugin-marketplace/plugins/linkedin-studio/docs/agents-capability-matrix.md
Kjell Tore Guttormsen 433c2efb3d fix(linkedin-studio): S11 — model-name declaration drift + model-consistency lint guard
Cold full-brief re-review (S10) reached a class the S7->S9 algorithm-stat lens
never did:

BLOCKER — post-feedback-monitor published as Haiku in four surfaces
(README:259, skills/linkedin-studio:159 with wrong color Green too,
skills/linkedin-analytics:41, agents-capability-matrix:20) while
agents/post-feedback-monitor.md runs Opus. v4.0.0's Opus promotion never
reached the user-facing tables. Synced all to Opus/Lime. Refreshed
agents-capability-matrix.md (frozen at the v2.0 14-agent era): header 14->19,
+5 missing longform agents, tier counts Opus 2->8 / Haiku 1->0, longform-gate
diagram updated to the real 8-Opus-agent chain.

MAJOR — de-branded docs/plan-fullspektrum-innholdsmotor.md:70 (model brand +
jan-2026 asserted as fact -> no-name/no-month relevance-model phrasing). It was
the only tracked survivor; the rest live in gitignored ROADMAP.md /
.claude/research/ (not shipped, out of honesty scope).

META — added Section 10 model-consistency guard
(scripts/check-model-consistency.mjs): each agents/*.md model: must match every
surface declaration AND the canonical rosters must list all 19 agents.
Permanent non-vacuity self-test + e2e mutation-proven.

Pre-patch sweep confirmed post-feedback-monitor was the sole drifted agent
(89 model rows, 0 other mismatches). test-runner.sh 68/0/0, node --test 94/94.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-05-30 15:05:37 +02:00

11 KiB
Raw Permalink Blame History

Agent Capability Matrix

19 specialized agents for LinkedIn content (short-form feed + long-form newsletter). Each agent has a focused responsibility, defined model, and unique color for visual identification.

Quick Reference

Agent Model Color Primary Responsibility
content-optimizer Sonnet Blue Optimize posts against algorithm signals
strategy-advisor Sonnet Green Growth strategy and phase-specific guidance
analytics-interpreter Sonnet Yellow Pattern discovery + weekly/monthly performance reports (interpret/report modes)
engagement-coach Sonnet Magenta 5x5x5 + first-hour tactics + CEA commenting + target selection
content-planner Sonnet Cyan Weekly/monthly content calendars
network-builder Sonnet Teal Strategic networking and outreach
content-repurposer Sonnet Purple Format conversion and evergreen refresh
trend-spotter Sonnet White Trending topics and opportunity scoring
voice-trainer Sonnet Pink Voice profile building and drift detection
differentiation-checker Sonnet Gray Originality scoring and commodity detection
video-scripter Sonnet Violet Video script creation with pacing and visual cues
post-feedback-monitor Opus Lime Post-publish 48h monitoring and real-time interventions
fact-checker Opus Brown Factual-claim verification against primary/credible sources (longform)
editorial-reviewer Opus Orange Editor's craft gate: prosa-håndverk + narrativ-arkitektur (longform)
persona-reviewer Opus Olive Reader-persona skeleton + resonance + hook-conversion gate (longform)
voice-scrubber Opus Red De-AI scrub + Norwegian-chronicle voice-drift correction (longform)
content-reviewer Opus Maroon Cold argument-integrity review (C1C5) on a frozen draft (longform)
language-reviewer Opus Navy Cold Norwegian-language review (L1L5) on a frozen draft (longform)
fact-reviewer Opus Gold Cold fact re-verification (F1F4) + pivot-risk on a frozen draft (longform)

Capability Matrix

Capabilities mapped across the 14 content-production agents (the columns below). P = Primary, S = Secondary/Supporting. The five remaining agents — editorial-reviewer, voice-scrubber, content-reviewer, language-reviewer, fact-reviewer — are ordered long-form quality gates rather than content-capability agents; they are documented in Longform Quality Gates below and listed in the Quick Reference above.

Capability optimizer strategy analytics engage planner network repurpose trends voice diff-check video post-monitor fact-check persona-rev
Post optimization P
Hook analysis P S S
Algorithm alignment P S S S
Growth strategy P S
Phase assessment P
Trajectory analysis P S
Audience analysis S P
Pattern discovery P
Performance reports P
Content DNA P S
Engagement coaching P S
5x5x5 method P S
Comment strategy P
CEA method P
Target identification P S
Content planning P S
Mix enforcement P
Gap analysis P
Network building S P
Connection scoring P
DM templates P
Format conversion P S
Evergreen scoring P
Content lifecycle S P
Trend scanning S P
First-mover assessment P
Angle mapping S S P
Voice profiling P
Drift detection P
Quarterly audit P
Originality scoring P
Commodity detection P
Differentiation P
Video scripting S P
Script pacing P
Visual cue notation P
Post-publish monitoring P
Velocity analysis P
Factual verification P
Primary-source check P
Persona resonance P
Hook-conversion gate P

Content Pipeline

How agents collaborate in the end-to-end content lifecycle:

┌─────────────┐    ┌──────────────────┐    ┌─────────────────┐
│ trend-spotter│───▸│  content-planner  │───▸│ diff-checker    │
│ (find topics)│    │ (plan + schedule) │    │ (originality    │
└─────────────┘    └──────────────────┘    │  gate ≥51/100)  │
                          │                 └────────┬────────┘
                          │                          │
                   ┌──────▼──────┐           ┌───────┴────────┐
                   │voice-trainer│           │  FORMAT SPLIT  │
                   │(voice check)│           └──┬──────────┬──┘
                   └──────┬──────┘              │          │
                          │             ┌───────▼───┐ ┌────▼─────────┐
                          │             │video-     │ │content-      │
                          └────────────▸│scripter   │ │optimizer     │
                                        │(scripts)  │ │(text posts)  │
                                        └───────┬───┘ └──────┬───────┘
                                                │            │
                                                └─────┬──────┘
                         ┌────────────────────────────┤
                         │                            │
                  ┌──────▼────────────┐       ┌────────▼───────┐
                  │analytics-         │       │  [PUBLISH]     │
                  │interpreter        │       └────────┬───────┘
                  │(interpret/report) │                │
                  └───────────────────┘       ┌────────▼───────┐
                                              │engagement-coach│
                                              │(5x5x5 + first  │
                                              │ hour + CEA     │
                                              │ commenting)    │
                                              └────────────────┘

Longform Quality Gates (newsletter)

For longform editions, eight Opus agents run as ordered gates BEFORE lock:

draft
  ─▸ fact-checker        (primary-source verification, post-cutoff web search)
  ─▸ editorial-reviewer  (craft: prosa-håndverk + narrativ-arkitektur, Step 5.5)
  ─▸ persona-reviewer    (skeleton → resonance → hook-conversion)
  ─▸ voice-scrubber      (de-AI + Norwegian-chronicle voice)
  ─▸ headless review     (Step 6.5 — COLD on the frozen draft):
        content-reviewer   (argument integrity C1C5)
        language-reviewer  (Norwegian language L1L5)
        fact-reviewer      (cold re-verification F1F4 + pivot-risk)
  ─▸ LOCK ─▸ delivery

Parallel Support Agents

These agents operate independently and feed into the pipeline at multiple points:

strategy-advisor ──────▸ Macro-level planning and phase guidance
analytics-interpreter ─▸ Pattern discovery + periodic reports feeding back into planning
network-builder ───────▸ Relationship building amplifying content reach
content-repurposer ────▸ Post-publish: extends content lifecycle

Which Agent Do I Need?

Scenario Agent Command
"I want to write a post" content-optimizer /linkedin:post
"What should I post about?" content-planner, trend-spotter /linkedin:pipeline
"Make this post better" content-optimizer /linkedin:post
"Is this original enough?" differentiation-checker /linkedin:pipeline
"Plan my week's content" content-planner /linkedin:batch
"Am I on track this week?" /linkedin:calendar
"How did I do this week?" analytics-interpreter (report mode) /linkedin:report
"Analyze my LinkedIn data" analytics-interpreter (interpret mode) /linkedin:analyze
"What's my LinkedIn strategy?" strategy-advisor /linkedin:strategy
"Help me engage more" engagement-coach /linkedin:strategy
"Who should I comment on?" engagement-coach /linkedin:strategy
"Build my network" network-builder /linkedin:strategy
"Does this sound like me?" voice-trainer /linkedin:post
"Repurpose my best post" content-repurposer /linkedin:pipeline
"What's trending in my field?" trend-spotter /linkedin:pipeline
"Audit my content strategy" analytics-interpreter, strategy-advisor /linkedin:audit
"How do I monetize?" strategy-advisor /linkedin:monetize
"Create a video script" video-scripter /linkedin:video
"Turn this post into a video" video-scripter, content-repurposer /linkedin:video
"Script a talking head video" video-scripter /linkedin:video
"Verify facts in this draft" fact-checker /linkedin:newsletter (longform)
"Will this land with my readers?" persona-reviewer /linkedin:newsletter (longform)

Model Selection Rationale

Model Agents Why
Opus 8 agents (fact-checker, editorial-reviewer, persona-reviewer, voice-scrubber, content-reviewer, language-reviewer, fact-reviewer, post-feedback-monitor) Longform judgment + 48h post-monitoring: factual verification, craft, resonance, voice, cold adversarial re-review, real-time intervention
Sonnet 11 agents Complex reasoning: optimization, strategy, analysis, scoring, scripting, comment targeting