> ## Documentation Index > Fetch the complete documentation index at: https://docs.plungeai.com/llms.txt > Use this file to discover all available pages before exploring further. # Experts, personas, backgrounds — shaping WHO the agent is in a run > Three capability kinds shape an agent's identity and framing (as opposed to skills, which shape its methods). All three inject into the front of the system prompt, in a fixed order, before anything else the run adds: Three capability kinds shape an agent's identity and framing (as opposed to skills, which shape its methods). All three inject into the **front** of the system prompt, in a fixed order, before anything else the run adds: ``` ## BACKGROUND: ← ambient truth, first, verbatim ← identity and voice ## EXPERT: ← labeled domain lenses ``` The order is load-bearing: backgrounds frame everything that follows, and putting them first keeps the prompt prefix stable across runs sharing a background (prompt caching). Experts are labeled sections precisely so the model can tell "domain lens" apart from "who I am". ## Backgrounds — always-on ambient context A **background** is a registry card whose body is standing context: company facts, product truth, an environment description. Injected FIRST and **verbatim** — no stripping — because ambient truth must arrive intact. ```yaml - type: harness goal: "Draft the Q3 partner update" mission: | Write the quarterly partner update. backgrounds: [acme-corp] ``` Use a background when every run in a family needs the same grounding ("what Acme is, our products, our tone"), instead of pasting boilerplate into each mission text. Backgrounds are per-owner resolvable: your private background card wins for your runs. ## Persona — one voice per run A **persona** is an identity/voice text (from the platform's persona store). Exactly **one** per run — a run speaks with one voice. ```yaml persona: analyst ``` Accepted spellings, all normalized to the same thing: `persona:` (canonical), `digital_twin:` (alias), and `personas: [x]` (plural from preset frontmatter — only the FIRST entry is used). If you list several personas, you did not get a blend; you got `personas[0]`. Personas also appear outside missions: `plungeai_execute_agent`/`POST /v1/agents/{id}/execute` accept a `persona` parameter, and CNL `debate`/`validate` blocks take `persona`/`digital_twin` per debater, judge, and validator — the same store, applied per role. That is the idiomatic way to run a multi-perspective panel: one debate block, different personas per debater. ## Experts — labeled domain lenses (UI name: Specialists) An **expert** is deep domain instruction material injected as a labeled `## EXPERT: ` section — "reason like a securities lawyer", "apply SRE practices". Up to **3** load eagerly per run. ```yaml experts: [securities-law, python-pro] ``` Persona vs expert, the practical line: persona = who the agent IS (voice, identity — one). Expert = what the agent additionally KNOWS HOW to judge (lenses — up to three eager). A hedge-fund panel is personas in a debate; a compliance review is one persona plus a law expert. ## Budgets and degradation (shared with skills) All eager identity/instruction text — backgrounds + persona + experts + skills — shares **one 24 KB budget**, with per-kind caps: 3 backgrounds, 1 persona, 3 experts (5 skills). Over cap or over budget, items **defer**: the prompt lists them under `## AVAILABLE ON DEMAND` and the agent can pull one mid-run with `load_skill` (matching type). Persona is never deferred — it either resolves or warns. Missing ids never fail the run; they degrade to warnings: - `background "" not found or empty` - `persona "" not found` - `expert "" not found` A run that "lost its voice" or ignored company context almost always has one of these warnings — check the run detail (`plungeai-results-traces`). The other classic cause: declaring more than the caps and assuming everything injected. Order lists by importance; the head injects, the tail defers. **Discover valid ids before declaring them** — the degrade-to-warning behavior means a guessed id fails silently: `plungeai_list_agents {kind: "experts", search: "…"}` or `{kind: "personas", search: "…"}` (REST: `GET /v1/discovery/search?kind=…&q=…`). ## Merge behavior in missions Like every mission field, these merge per key with **last-wins** across pre-built card → workflow root → task, and **arrays REPLACE rather than union** (see `plungeai-missions`). So a task-level `experts: [x]` replaces the card's expert list — and an explicit empty `experts: []` deliberately clears it. To ADD to a card's list you must restate the full list. ## Authoring guidance - Keep each body lean and self-contained: it lands in a prompt with everything else competing for 24 KB. A 15 KB background starves persona and experts. - Backgrounds: facts, not instructions. Instructions belong in mission text or skills — a background that says "always do X" fights the mission's own framing. - Experts: method and judgment criteria ("what a great X checks first"), not essays. - Test identity injection cheaply: run a `quick`-effort mission whose goal is to introduce itself and state its operating context; the answer shows exactly which layers landed.