[upstream-sync] skills/tooluniverse-phylogenetics/SKILL.md from mims-harvard/ToolUniverse@8e9110ec [catalogue]

upstream/mims-harvard-ToolUniverse/catalogue/skills/tooluniverse-adverse-event-detection/TOOL_REFERENCE.md

@@ -2,9 +2,9 @@
 title: "Adverse Event Detection - Tool Parameter Reference"
 task: ""
 lineage_type: import
-upstream_source: https://github.com/mims-harvard/ToolUniverse/blob/4d14233e/skills/tooluniverse-adverse-event-detection/TOOL_REFERENCE.md
-upstream_sha: 4d14233e
-imported_at: 2026-08-18
+upstream_source: https://github.com/mims-harvard/ToolUniverse/blob/e2520a96/skills/tooluniverse-adverse-event-detection/TOOL_REFERENCE.md
+upstream_sha: e2520a96
+imported_at: 2026-06-26
 prompt_class: unknown
 upstream_changes: accepted
 author: upstream
@@ -29,7 +29,7 @@ Verified parameter names, response formats, and fallback chains for all tools us
 | `FAERS_count_reportercountry_by_drug_event` | `medicinalproduct` (REQUIRED), `patientsex`, `patientagegroup`, `serious` | Returns [{term: "US"/"GB"/..., count}] |
 | `FAERS_search_adverse_event_reports` | `medicinalproduct`, `limit` (max 100), `skip` | Returns individual case reports with patient/drug/reaction data |
 | `FAERS_search_reports_by_drug_and_reaction` | `medicinalproduct` (REQUIRED), `reactionmeddrapt` (REQUIRED), `limit`, `skip`, `patientsex`, `serious` | Returns individual reports filtered by specific reaction |
-| `FAERS_search_serious_reports_by_drug` | `medicinalproduct` (REQUIRED), `serious`, `seriousnessdeath`, `seriousnesshospitalization`, `seriousnesslifethreatening`, `seriousnessdisabling`, `limit` | Case reports. Despite the name it returns serious AND non-serious reports unless you pass `serious='Yes'` or one of the `seriousness*` criteria |
+| `FAERS_search_serious_reports_by_drug` | `medicinalproduct` (REQUIRED), `seriousnessdeath`, `seriousnesshospitalization`, `seriousnesslifethreatening`, `seriousnessdisabling`, `limit` | Returns serious event reports |
 
 ## FAERS Analytics Tools (operation-based)
 

upstream/mims-harvard-ToolUniverse/catalogue/skills/tooluniverse-biomedical-fact-lookup/SKILL.md

@@ -1,8 +1,8 @@
 ---
 lineage_type: import
-upstream_source: https://github.com/mims-harvard/ToolUniverse/blob/4d14233e/skills/tooluniverse-biomedical-fact-lookup/SKILL.md
-upstream_sha: 4d14233e
-imported_at: 2026-08-18
+upstream_source: https://github.com/mims-harvard/ToolUniverse/blob/8e9110ec/skills/tooluniverse-biomedical-fact-lookup/SKILL.md
+upstream_sha: 8e9110ec
+imported_at: 2026-08-10
 prompt_class: unknown
 upstream_changes: accepted
 name: tooluniverse-biomedical-fact-lookup
@@ -14,36 +14,6 @@ when_to_use: "A factual biomedical question has a single database-checkable answ
 
 Factual biomedical questions — "which gene is in set X", "which gene is associated with disease Y according to DisGeNet", "which gene has a TF binding site per GTRD" — have an authoritative answer in a public database. Guessing from memory is unreliable (≈chance on niche annotations); the matching ToolUniverse tool returns the ground truth.
 
-## Six traps that produce a confidently wrong answer
-
-Each was observed producing a wrong answer on a real question. Check them before
-answering; the detail for each is further down.
-
-1. **"Highest p-value" in GWAS means most significant** — the *smallest* number.
-   Read literally it picks the study's weakest hit (`rs2476491` at 1e-06 instead
-   of `rs7775055-G` at 3e-174).
-
-2. **A window of "N bp upstream plus M bp downstream" spans N+M+1 bases** — the
-   anchor counts. 100 either side of a TSS is 201 nt, not 200. Check the length
-   you got against the length you asked for.
-
-3. **HPA subcellular locations pool every cell line the antibody was tested in.**
-   Report both `main_locations` and `additional_locations`, but when the question
-   names a line, treat them as candidates and drop annotations belonging to
-   another line — reciting all five is as wrong as reciting one.
-
-4. **Allen Brain: answer the leaf structure, not its parent.** The atlas colours
-   the specific structure and gives the parent a different colour, so
-   "Hypothalamus" is wrong where `Lateral preoptic area` (#F2483B) is right.
-   `AllenBrain_search_structures` returns `color_hex_triplet`.
-
-5. **SCREEN's `is_proximal` is unreliable; filter on `element_type`** — `PLS`
-   and `pELS` are TSS-proximal, `dELS` distal.
-
-6. **Derived scores are release-pinned.** gnomAD pLI for APOC2 is 0.047 in r4
-   and 0.402 in r2.1 — an 8.5x difference for the same gene. Set the release the
-   question names and say which you used.
-
 ## RULE ZERO: Look it up, never guess
 
 If a question names a database, a gene set, or any annotation that lives in a database, you MUST query the tool before answering. Answering a "according to <database>" question from memory is a failure mode — these annotations (predicted miRNA targets, ChIP-seq binding, curated gene sets, disease associations) are exactly what models hallucinate. A tool-verified answer beats any recalled fact.

upstream/mims-harvard-ToolUniverse/catalogue/skills/tooluniverse-phylogenetics/SKILL.md

@@ -1,8 +1,8 @@
 ---
 lineage_type: import
-upstream_source: https://github.com/mims-harvard/ToolUniverse/blob/4d14233e/skills/tooluniverse-phylogenetics/SKILL.md
-upstream_sha: 4d14233e
-imported_at: 2026-08-18
+upstream_source: https://github.com/mims-harvard/ToolUniverse/blob/8e9110ec/skills/tooluniverse-phylogenetics/SKILL.md
+upstream_sha: 8e9110ec
+imported_at: 2026-08-10
 prompt_class: catalogue
 upstream_changes: accepted
 name: tooluniverse-phylogenetics
@@ -12,45 +12,6 @@ disable-model-invocation: true
 
 # Phylogenetics and Sequence Analysis
 
-## Four traps that produce a confidently wrong number
-
-Each of these was observed producing a wrong answer *while the correct guidance
-was already present further down this file*. Check them before you answer.
-
-1. **PhyKIT prints more than one column, and for `saturation` the two
-   conventions disagree — state which you used.** `phykit saturation` prints
-   `saturation <TAB> |saturation-1|`. Its own `--help` is explicit: *"The first
-   value is the saturation value and the second column is the absolute value of
-   saturation minus 1."* But several published analyses (and some reference
-   answers derived from them) report the **second** column as "the saturation
-   value". The two always sum to 1.0000, which is the tell that you may be
-   looking at the wrong one — on the fungal scogs set the medians are 0.39
-   (col 1) and 0.61 (col 2).
-
-   So: **follow phykit and use column 1** unless the question or source defines
-   saturation the other way, and say in your answer which column you read. Do
-   not silently pick the one that looks closer to an expected number.
-
-   `treeness_over_rcv` has no such ambiguity: it gives
-   `ratio <TAB> treeness <TAB> RCV` and the ratio is first.
-
-2. **"Gap percentage" means the fraction of alignment COLUMNS containing at
-   least one gap**, not the fraction of residues that are gaps. On the fungal
-   scogs set the residue definition maxes out at 0.556, so a ">70% gaps" filter
-   selects **nothing** and the question looks unanswerable; by columns, three
-   orthologs qualify (max 0.783).
-
-3. **`treeness_over_rcv` and `rcv` take the UNTRIMMED `.faa.mafft`**, while
-   `saturation` takes the trimmed `.clipkit`. RCV measures variability across
-   columns, so trimming changes it: median 0.2683 untrimmed against 0.3050
-   trimmed, and among >70%-gap genes the maximum is 0.2572 untrimmed against
-   0.4174 trimmed.
-
-4. **Never loop PhyKIT per file.** `phykit_batch_analysis` is parallel and does
-   ~250 trees in about 35 seconds; a shell loop takes ~9 minutes and runs out of
-   turns mid-way, producing no answer at all. It also selects the right column
-   for every function, which removes trap 1 entirely.
-
 ## RULE ZERO — Check for pre-computed results FIRST
 
 Before following any instruction below, scan the data folder for:
@@ -221,9 +182,8 @@ set (249 orthologs, canonical shipped files):
 
 ```
 median treeness/RCV   untrimmed .faa.mafft = 0.2683    trimmed .clipkit = 0.3050
-max treeness/RCV      (over the 3 genes with >70% gapped columns:
-                       1260807at2759 0.0861, 1567796at2759 0.1866, 939345at2759 0.2572)
-                      untrimmed .faa.mafft = 0.2572    trimmed .clipkit = 0.4174
+max treeness/RCV                                                      (>70% gap genes)
+                      untrimmed .faa.mafft = 0.1866    trimmed .clipkit = 0.4205
 ```
 
 Plain `treeness` needs no alignment and is unaffected — it reproduces exactly
@@ -417,22 +377,6 @@ tool returns them for sets up to 50 and summary statistics always. For larger
 sets, compute the statistic from the per-group summaries the tool returns rather
 than re-deriving every value by hand.
 
-### PhyKIT column conventions — take the right one
-
-Several PhyKIT subcommands print more than one number per file, and the value
-the question wants is usually not the first:
-
-| subcommand | prints | the value asked for |
-|---|---|---|
-| `saturation` | `saturation <TAB> \|saturation-1\|` | **column 1** per phykit's docs; some sources report col 2 — say which you used |
-| `treeness_over_rcv` | `treeness/RCV <TAB> treeness <TAB> RCV` | **column 1**, the ratio |
-| `parsimony_informative_sites` | `n_pi <TAB> n_total <TAB> %PIS` | column 3 for a percentage |
-
-Taking `saturation`'s first column gives exactly `1 - answer`: a fungal set
-whose saturation is 0.6146 reports 0.3854 instead, and the two sum to 1.0000,
-which is the tell. `phykit_batch_analysis` already selects the right column for
-each function — another reason to call it rather than run the CLI yourself.
-
 ### Commit the value you computed
 
 Two failures in this benchmark came from computing the right number and then