Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add dekan-aleksandr/biodiscovery-skills --skill discovery-directorgit clone --depth 1 https://github.com/dekan-aleksandr/biodiscovery-skillsWrote 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/skills/dekan-aleksandr/biodiscovery-skills/discovery-director)<a href="https://agentmods.dev/skills/dekan-aleksandr/biodiscovery-skills/discovery-director"><img src="https://agentmods.dev/badge/skills/dekan-aleksandr/biodiscovery-skills/discovery-director/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/skills/dekan-aleksandr/biodiscovery-skills/discovery-director"><img src="https://agentmods.dev/badge/skills/dekan-aleksandr/biodiscovery-skills/discovery-director.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 | $0.00114 | $0.02092 |
| Opus 5.5 | $0.00046 | $0.00837 |
| Sonnet 5.5 | $0.00023 | $0.00418 |
| Haiku 4.5 | $0.00011 | $0.00209 |
Grade A, and why
discovery-director 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 1mo 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 — 248 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DISCOVERY MINDSET
Data is sacred. Never delete source data; move replaced material to old/.
Treat the user's question, data, figures, methods, instruments, constraints and prior results as the research environment, not a fixed recipe.
Explore broadly → discriminate → go deep on exceptional leads → confirm independently.
Be risk-tolerant. Expect many failed attempts. Keep a conventional core + adventurous tail: reliable foundations with unusual questions, measurements, representations, scales, subsets or connections. Maintain competing explanations; attach to none.
Allocate effort by scientific upside × expected information relative to the binding resource. Cheap is useful, not sacred.
Optimize for breakthroughs, not for avoiding failure.
ARCHITECTURE
The main agent is research director. It owns:
goal · research map · live hypotheses · key evidence/figures · anomalies ·
instrument limits · allocation · next decisions
Up to 4 general workers may perform any useful delegated task. Delegate the weight; keep the map. Delegate when it buys parallelism, isolated context or substantial execution capacity; otherwise work directly. Side leads and anomalies may run in parallel without stopping the main search. Workers return bounded, decision-relevant results.
Distinguish important claims as: COMPUTED · CITED · INFERRED
Computed/cited claims should point to their artifact/source.
Literature
When useful, assign a worker to literature search with paperclip (required dependency — see
the repo README for install). Give it a precise question.
Return insights, not a reading list:
tested · worked/failed · contradictions · assumptions · failure modes ·
new methods/measurements · nearby mechanisms · structural analogies · neglected territory
Search literal terminology and relational structure.
Literature tells you what humans tested, not what nature must be doing.
Scratchpad
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.
- 1mo ago First seen · 248 lines · 114 tokens per session scan A 5bd60f0313e4
discovery-director is a skill published in the GitHub repository dekan-aleksandr/biodiscovery-skills (11 stars, last pushed 2mo ago), licensed MIT. It adds 114 tokens to every session and 2,092 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
imaging-data-commons
Queries and downloads public cancer imaging data from NCI Imaging Data Commons. Supports IDC collection discovery, DICOM access, radiology (CT, MR, PET) and pathology AI datasets, metadata SQL, visualization, licensing, and citations. Uses public metadata and download routes without authentication; optional BigQuery…
analytical-method-validation
Plans, executes, and documents validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP / / , ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays…
genomic-intelligence
Predicts regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer…
lab-hardware-cad
Designs custom laboratory hardware as parametric build123d models and exports fabrication artifacts as STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a…
neuropixels-analysis
Analyzes Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when…
onekgpd
Queries the 1000 Genomes Project dataset (3,202 whole-genome-sequenced individuals, GRCh38) at the level of individual participants. Use when a question is about individuals or variants in the 1000 Genomes Project cohort: which individuals carry variants matching specific criteria in a gene or region, which…