Skip to content
FunCoding

Search

Search docs, Skills and MCP

minutes-graph

Policy-safe relationship rankings, commitments, aliases, person profiles, and topic research. Always use Minutes' bounded native CLI surfaces; never build or read a durable graph cache.

科研1.5k.opencode/skills/minutes-graph/SKILL.md

Install

Send this to Claude Code, Codex or Cursor. The agent checks the Skill for safety first and installs it only after you confirm.

读取 https://funcoding.ai/skills/silverstein/minutes/opencode-skills-minutes-graph/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

/minutes-graph

Minutes builds relationship rankings, exact person profiles, and commitments from one supervised, process-private SQLite projection of stable policy-authorized Markdown plus confirmed identity corrections. One ordered snapshot authority spans corpus and corrections, and the worker is hard-limited for memory, output, and wall time. Topic research uses the separately bounded live-source search boundary. Both paths re-attest policy before returning facts. Do not fall back to a retired durable index or read meeting files directly.

Privacy boundary

  • Never walk meeting files, parse frontmatter yourself, or read raw transcripts for this skill.
  • Never run graph_build.py or read ~/.minutes/graph/index.json; those are retired legacy surfaces.
  • Never create a replacement graph cache, spreadsheet, JSON file, or database.
  • Never pass --include-restricted. Restricted meetings are intentionally absent from this agent-facing skill.
  • Treat any authorization, resource-budget, correction-race, or projection error as a hard stop. Do not fall back to filesystem reads.

Available commands

  • minutes people --json — bounded relationship rankings and losing-touch signals.
  • minutes commitments --json — bounded graph commitments.
  • minutes people merge <canonical> <alias...> — confirm an identity correction in the local vocabulary; uncertain names are never merged automatically.
  • minutes person "<name>" — bounded person profile.
  • minutes research "<topic>" — bounded topic research.

Workflow

  1. Classify the request and use the narrowest command above.
  2. Require exit status 0. Use only the bounded native result and never substitute filesystem reads.
  3. For a proposed alias, show the suggestion and ask for confirmation before running minutes people merge; a wrong merge is worse than no merge.
  4. Do not imply that restricted history or a relationship fact is absent when any command fails.

Output

Return only the bounded native result. Never invent rankings, commitments, or relationship signals from raw files.

Gotchas

  • A failed person profile cannot be interpreted as “never met.” Report the source unavailable.
  • Do not imply that a later sensitivity change proves a historical fact absent; report only the current authorized projection.
  • Alias suggestions are evidence, not permission to rewrite identity. Require explicit confirmation before merging.
  • Use minutes research "<topic>" for bounded company, product, or topic research. If it fails, report the source unavailable; never fall back to raw corpus reads.

Similar Skills

lead-research-assistant
ComposioHQ/awesome-claude-skills77k

lead-research-assistant

Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.

Science

13c-metabolic-flux
K-Dense-AI/scientific-agent-skills48k

13c-metabolic-flux

Estimates intracellular metabolic fluxes from steady-state carbon-13 isotope-tracing measurements using validated atom maps, mfapy isotope simulation, constrained multistart fitting, and flux-profile diagnostics. Use for 13C-MFA, carbon tracing, mass isotopomer distributions (MDVs/MIDs), positional isotopomers, parallel tracer experiments, and determining whether labeling data constrain a pathway flux. Distinguishes measured-label inference from COBRA flux balance analysis and flags experiments requiring nonstationary MFA.

Science

datamol
K-Dense-AI/scientific-agent-skills48k

datamol

Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.

Science

biopython
K-Dense-AI/scientific-agent-skills48k

biopython

Provides Biopython workflows for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Supports batch processing, custom molecular-biology pipelines, BLAST automation, structure analysis, and motif analysis.

Science

bulk-rnaseq
K-Dense-AI/scientific-agent-skills48k

bulk-rnaseq

Prepares bulk RNA-seq FASTQ, Salmon, STAR or featureCounts output for gene-level differential expression. Covers nf-core/rnaseq and standalone quantification, biological replication, strandedness, reference provenance, validated count assembly and a PyDESeq2 handoff. Use for FASTQ-to-counts analysis, nf-core/rnaseq configuration, STAR/Salmon quantification, or building a counts matrix for DESeq2. For single-cell data use scanpy; for statistical fitting alone use pydeseq2.

Science

alphagenome
K-Dense-AI/scientific-agent-skills48k

alphagenome

Looks up precomputed AlphaGenome Atlas effects for any GRCh38 single-nucleotide variant (AVI score with Phred and 18 SHAP feature attributions, plus raw and quantile scores for RNA-seq, DNase, ATAC, ChIP-TF, ChIP-histone, CAGE, PRO-cap, splicing, polyadenylation and contact-map tracks), scores variants or scans windows on demand with the AlphaGenome model for human and mouse (variant scoring, in silico mutagenesis, REF-versus-ALT track prediction), and builds Atlas website deep links. Use when the user mentions AlphaGenome, AlphaGenome Atlas, AVI or AlphaGenome Variant Impact, DeepMind variant effect prediction, or wants to prioritise or mechanistically interpret non-coding, regulatory, splicing, enhancer, promoter, or chromatin-accessibility effects of SNVs from a VCF, credible set, or region. Research use only; not a clinical tool.

Science