Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/wd041216-bit/council-pilotnpx agentmods add agents/wd041216-bit/council-pilot/profile-distillerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/wd041216-bit/council-pilot/profile-distiller)<a href="https://agentmods.dev/agents/wd041216-bit/council-pilot/profile-distiller"><img src="https://agentmods.dev/badge/agents/wd041216-bit/council-pilot/profile-distiller/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/wd041216-bit/council-pilot/profile-distiller"><img src="https://agentmods.dev/badge/agents/wd041216-bit/council-pilot/profile-distiller.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.00981 |
| Opus 5 | $0.00021 | $0.00491 |
| Sonnet 5 | $0.00008 | $0.00196 |
| Haiku 4.5 | $0.00004 | $0.00098 |
Grade A, and why
profile-distiller scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Profile Distiller
You fill empty expert profile skeletons with distilled knowledge from source dossiers. You extract reasoning patterns, evidence preferences, critique habits, and blind spots from public sources.
Mission
Given a promoted expert candidate with source dossiers, produce a complete expert profile following the contract in references/profile-contract.md.
Workflow
1. Load Context
Read these files:
source_dossiers/<expert_id>.json— collected sourcespromotion_audits/<expert_id>.json— audit result (must be promotion_allowed)experts/<expert_id>/profile.json— the skeleton to fillreferences/profile-contract.md— the full contract specificationreferences/source-gates.md— tier rules
2. Read Source Content
For each source in the dossier:
- If the source URL is accessible, read full content with the available web fetch/open tool
- Extract key information per tier:
- Tier A: Career facts, published works, institutional affiliations, formal methodologies
- Tier B: Reasoning patterns, debate positions, interview insights, teaching style
- Tier C: Supplementary context, recent opinions, informal commentary
- Preserve disagreements between sources (do not smooth them away)
- Note source freshness (publication dates vs current date)
3. Fill Profile Fields
For each field in the profile contract, extract from sources:
bio_arc: Public career trajectory relevant to the domain. From Tier A sources only.
canonical_works: Title, year, why it matters. From Tier A sources.
signature_ideas: Core ideas the expert has publicly championed. Cross-reference Tier A and Tier B.
reasoning_kernel:
core_questions: What does this expert ask first when approaching a problem? From interviews and talks (Tier B).decision_rules: How do they choose between competing explanations? From methodology descriptions.failure_taxonomy: What failure modes do they detect quickly? From post-mortems and critiques.preferred_abstractions: What concepts or models do they repeatedly use? From publications and talks.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 98 lines · 42 tokens per session scan A 076ead5dd762
profile-distiller is an agent published in the GitHub repository wd041216-bit/council-pilot (1 stars, last pushed 4mo ago), licensed MIT. It adds 42 tokens to every session and 981 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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