person_profile ยท diff
git:20260905.97621c1 to git:20260906.f9cef19
43 added, 45 removed. Audit A to A.
---
name: person_profile
- description: Collate a comprehensive profile on a specific person by searching a given dataset, returning the full synthesized report.
+ description: Generate individual profiles from an existing person roster, LinkedIn enrichment and dataset evidence, including founder-trait assessment for active founders. Use for selected people or the complete roster.
---
- ## Skill Prompt: `person_profile`
+ # Person profile
- **Objective:** Collate a comprehensive profile on a specific person by searching a given dataset, returning the full synthesized report.
+ Generate standard individual profiles for use directly or by other skills.
- **Inputs:**
- * `name`: A string representing the person's name (e.g., `"John Doe"`).
- * `dataset_name`: The target dataset to search (e.g., `"fabas"`).
+ ## Inputs and outputs
- **Procedure:**
+ The async API accepts `dataset_name`, optional `names` (a string or list),
+ and keyword-only `include_dataset_context=True`. Omitted names select everyone
+ in the roster. `person_profile` returns `list[InsightFile]`; the
+ `person_profile_as_person_objects` adapter runs the same workflow and returns
+ populated `list[Person]`.
- 1. **Insight File & Caching:**
- * Resolve the person to its canonical identifier through the standard person-resolution flow.
- * Construct the profile insight with `lib.insights.InsightFile(dataset=dataset_slug, skill="person_profile", model=<model>, identifier=<person_identifier>, subdir=True, config_key=<query_and_instructions>)`.
- * Use `insight.find(selection="reusable")` and `insight.content()` to reuse a fresh existing profile when available; otherwise generate the profile and persist it with `insight.save(...)`. Do not hardcode `<REPO_PATH>/insights/...` paths.
+ Explicit unmatched names currently create sparse `Person` inputs for profiling;
+ they do not change the roster. The roster remains required even for these calls.
- 2. **Data Retrieval & Synthesis:**
- * Read the existing manual roster and enrich its people through `LinkedInResolver`.
- * Synchronize the dataset before checking profile freshness.
- * Load `query`, `llm_instructions`, and `founder_traits_instructions` via
- `load_repository_config("person_profile")`; both instruction sections always
- form the standard prompt and freshness key.
- * On a cache miss, use `build_person_dossier` for dataset evidence when
- `include_dataset_context` is enabled, add the resolved LinkedIn payload,
- and synthesize through `generate_markdown`.
+ ## Workflow and dependencies
- 3. **Output Generation:**
- * Save every synthesized profile through `InsightFile`.
- * `person_profile(...)` returns a flat `list[InsightFile]`.
- * `person_profile_as_person_objects(...)` runs the same workflow and returns
- the populated `list[Person]` required by person-oriented composition.
+ Read the existing roster, resolve LinkedIn profiles and synchronize the dataset
+ before selecting reusable individual profiles. On a cache miss, combine the
+ resolved LinkedIn payload with `build_person_dossier` evidence when
+ `include_dataset_context` is enabled, then synthesize the profile.
- **CLI Interface:**
- * Expose this skill through the shared slash-command harness.
+ Biographical and founder-trait instructions always belong to the standard prompt.
+ Apply the trait assessment only to explicitly identified active founders; keep
+ other people factual. [Shared profile standards](../standards_and_architecture/SKILL.md#standard-person-profiles)
+ own identifiers, filenames, manual precedence and compatibility between consumers.
- ## Usage
+ Direct calls never discover people. Run [persons_in_dataset](../persons_in_dataset/SKILL.md)
+ first when the roster is missing; bulk refresh declares that dependency.
- Both `person_profile(...)` and `person_profile_as_person_objects(...)` use the
- same standard generation workflow: read the authoritative manual roster, resolve
- LinkedIn profiles, gather dataset evidence, and apply the configured biographical
- and founder-trait instructions. Founder traits are assessed for explicitly
- identified active founders; unsupported assessments report insufficient information.
- A missing roster raises an error directing the caller to run `persons_in_dataset`;
- profile generation never discovers people.
+ ## Side effects and failure behavior
- Every profile uses `<identifier>-<model>.md`, with the identifier selected by
- `Person.identifier`: LinkedIn ID, otherwise email address, otherwise full name,
- using standard slugification. The retained `include_dataset_context` option affects
- freshness metadata, never filenames. Manual overrides retain their normal precedence.
+ LinkedIn resolution can fetch profiles and update stored JSON and registry state.
+ Resolution and synchronization occur even before a manual or reusable profile
+ is selected. Generation settings affect freshness metadata, not filenames.
- ```bash
- conda run -n sictic-env python -m skills.harness /person_profile "<DATASET_NAME>" "<NAME>"
+ A missing or invalid roster raises. An empty roster with no explicit names
+ returns `[]`. With no dossier, mentions or LinkedIn payload, generation saves a
+ profile with a no-information note. Individual generation failures are collected:
+ successful files remain, but the API raises instead of returning a partial list.
- conda run -n sictic-env python -m skills.person_profile \
- --dataset "<DATASET_NAME>" \
- --person "<NAME_1>, <NAME_2>"
+ ## Usage
+
+ The harness requires a person; the direct CLI also supports the complete roster.
+
+ ```bash
+ conda run -n sictic-env python -m skills.harness /person_profile "<DATASET>" "<NAME>"
+ conda run -n sictic-env python -m skills.person_profile --dataset "<DATASET>"
+ conda run -n sictic-env python -m skills.person_profile --dataset "<DATASET>" --person "<NAME_1>, <NAME_2>"
```
- Person discovery is owned by `skills/persons_in_dataset`. This skill uses the library roster reader, then gathers evidence and writes individual profiles. Only an explicit discovery run creates a missing roster.
+ ## References
+
+ - [Implementation and adapter](person_profile.py)
+ - [Profile prompts and query](../../config/person_profile/)
+ - [LinkedIn resolution contract](../standards_and_architecture/SKILL.md#linkedin-retrieval-and-persistence)