Guide for creating DAAF agent definition files. Covers 12-section template, hook registration, skills-in-frontmatter, integration checklist. Use when adding or revising agents. For SKILL.md files, use skill-authoring instead.
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NCCS — Form 990 data for private nonprofit colleges (Portal: IPEDS-matched, 1993-2016). Revenue, expenses, assets, endowment, governance beyond IPEDS. Use when IRS financial depth needed. Portal ends 2016; public institutions excluded (no Form 990).
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
National Center for Charitable Statistics (NCCS) Form 990 data for private nonprofit colleges and universities (Portal mirror: IPEDS-matched institutions, 1993-2016). Use when IRS-based financial data — revenue, expenses, assets, endowment details — or governance information (board composition, executive compensation) is needed beyond what IPEDS provides. Portal data ends at 2016; for newer direct-source data, use the official NCCS Core catalog, whose merged Core currently covers 1987-2024 and whose SOI-current panel covers 2012-2024. Tax year 2024 is provisional, and recent years remain in progress as late and amended returns arrive. Public institutions do not file Form 990 and are excluded.
The NCCS (National Center for Charitable Statistics) is the principal U.S. repository for empirical data on the nonprofit sector, derived from IRS Form 990 filings. It provides financial depth, governance detail, and historical coverage for private nonprofit colleges and universities that goes well beyond what IPEDS collects.
CRITICAL: Value Encoding
The Education Data Portal encodes ALL categorical variables as integers, not strings. Variable names are lowercase in Portal data. Always verify codes against codebooks.
Context fipsmult_ein_flagPortal integer 6(California)1(Yes)Original NCCS "06"or stringN/A See
./references/variable-definitions.mdfor complete encoding tables.
| File | Purpose | When to Read |
|---|---|---|
nonprofit-data.md | NCCS datasets and what they contain | Understanding available data sources |
form-990.md | IRS Form 990 structure and data elements | Understanding what information is collected |
education-relevance.md | How NCCS relates to higher education | Connecting nonprofit data to education research |
ntee-codes.md | Nonprofit classification system | Finding and filtering educational institutions |
variable-definitions.md | Key financial and organizational variables, codes, special values | Interpreting specific data elements or building queries |
Research need?
├─ Financial data for private colleges → ./references/form-990.md
│ ├─ Revenue breakdown → Part VIII (Statement of Revenue)
│ ├─ Expenses by function → Part IX (Statement of Functional Expenses)
│ ├─ Assets and liabilities → Part X (Balance Sheet)
│ └─ Endowment details → Schedule D
├─ Governance/leadership → ./references/form-990.md
│ ├─ Board members → Part VII (Compensation)
│ ├─ Executive compensation → Part VII, Schedule J
│ └─ Policies and procedures → Part VI (Governance)
├─ Organizational characteristics → ./references/nonprofit-data.md
│ ├─ Basic info (name, address, EIN) → BMF
│ ├─ Tax-exempt type → BMF (SUBSECCD)
│ └─ NTEE classification → BMF (NTEECC)
└─ Identify institutions → ./references/ntee-codes.md
├─ All higher education → NTEE B40-B50
├─ Universities → B40, B41, B42, B43
└─ Community colleges → B44
Dataset selection?
├─ Need universe of all nonprofits?
│ └─ Business Master File (BMF) → ./references/nonprofit-data.md
├─ Need detailed financial variables?
│ ├─ Large organizations (full 990 filers) → Core PC files
│ ├─ All organizations (990 + 990EZ) → Core PZ files
│ └─ Maximum detail (2000+ fields) → Efile database
├─ Need private foundations?
│ └─ Core PF or 990-PF Efile data
└─ Need small grassroots orgs?
└─ 990-N ePostcard database
Linking NCCS to education data?
├─ Need to match to IPEDS?
│ └─ See ./references/education-relevance.md (EIN-UNITID crosswalk)
├─ Need geographic analysis?
│ └─ Use BMF geocoded addresses + Census crosswalks
├─ Want institutional comparisons?
│ └─ Filter by NTEE codes B40-B50 for higher ed
└─ Analyzing trends over time?
└─ Use the official Core catalog; choose merged Core (1987-2024) or SOI-current (2012-2024) and record provisional/in-progress status
Portal mirror (via fetch_from_mirrors()):
| Dataset | Description | Coverage | Rows |
|---|---|---|---|
990 Forms (nccs/colleges_nccs_all) | Form 990 data for higher ed institutions matched to IPEDS | 1993-2016, ~2,600 institutions | ~30K |
Direct NCCS sources (outside Portal):
| Dataset | Description | Current Catalog Coverage | Key Use |
|---|---|---|---|
| Merged Core | Harmonized Form 990/990-EZ financial records | 1987-2024 | Broad historical financial analysis |
| SOI-current Core | Current-panel Core files | 2012-2024 | More recent annual analysis |
| Business Master File (BMF) | Tax-exempt organization registry | Verify in current BMF catalog | Sampling frame, basic information |
| IRS 990 Efile | Full electronic filings with detailed fields | Verify in current Efile catalog | Detailed governance and programs |
Direct-source status (verified 2026-07-21): Tax year 2024 is provisional, and recent tax years remain in progress as late and amended returns arrive. Start at the official Core catalog,
https://urbaninstitute.github.io/nccs/catalogs/catalog-core.html, and record the selected product, tax years, retrieval date, and provisional/in-progress status.Scope note: The Portal mirror contains only Form 990 data matched to IPEDS institutions (~2,600 institutions), fixed at 1993-2016. It does NOT include the broader nonprofit universe or NTEE fields. For non-education nonprofits, NTEE-based filtering, or newer tax years, select the appropriate direct product from the official NCCS catalogs rather than treating "NCCS" as one undifferentiated dataset.
Portal dataset:
| ID | Format | Level | Example | Notes |
|---|---|---|---|---|
unitid | Integer | Institution | 110635 | IPEDS institution ID (Portal addition) |
ein | Integer | Organization | 10211484 | Employer Identification Number |
fips | Integer | State | 6 (California) | State FIPS code |
Full NCCS (direct download, outside Portal):
| ID | Format | Level | Example | Notes |
|---|---|---|---|---|
EIN | 9-digit number | Organization | 123456789 | Unique to each nonprofit |
NTEECC | Letter + 2 digits | Classification | B42 (4-year college) | May be imprecise (~25%); NOT in Portal data |
SUBSECCD | 2-digit code | Tax subsection | 03 (501(c)(3) charity) | NOT in Portal data |
FIPS | 5-digit code | Geography | 06037 (LA County) | State + county; Portal uses state-level integer |
| Code | Description |
|---|---|
| B20-B29 | Elementary & Secondary Schools |
| B40 | Higher Education Institutions (General) |
| B41 | Two-Year Colleges |
| B42 | Undergraduate Colleges (4-year) |
| B43 | Universities |
| B50 | Graduate/Professional Schools |
| B60 | Adult/Continuing Education |
| B70 | Libraries |
| B80 | Student Services/Organizations |
| B90 | Educational Services/Schools N.E.C. |
The Portal dataset has 161 columns. Key mappings from original NCCS/990 names to Portal lowercase names:
| Portal Name | Original NCCS/990 | Description |
|---|---|---|
year | FISYR | Academic year (fall semester) — Portal-aligned year (1993-2016) |
fiscal_year | — | IRS fiscal year ending year from 990 filing (1994-2017); typically year + 1 |
unitid | — | IPEDS institution ID (Portal addition) |
ein | EIN | Employer Identification Number |
fips | FIPS | State FIPS code (integer) |
inst_name_nccs | NAME | Organization name from 990 filing |
mult_ein_flag | — | Multiple-EIN indicator (0=No, 1=Yes) |
contributions_total | CONT | Total contributions |
prog_serv_rev | PROGREV | Program service revenue |
revenue_total | TOTREV | Total revenue |
expenses_total | EXPS | Total expenses |
total_assets_eoy | TOTASS | Total assets (end of year) |
net_assets_eoy | NETASS | Net assets (end of year) |
compensation_officers | COMPENS | Officer compensation |
salaries_other | OTHSAL | Other salaries |
Note: The full 161 columns include detailed revenue breakdowns (Part VIII), expense breakdowns (Part IX), and balance sheet items (Part X). Consult the codebook for the complete list. Use
get_codebook_url("nccs/codebook_colleges_nccs_form_990")fromfetch-patterns.mdto download it.
| Code | Meaning | When Used |
|---|---|---|
-1 | Data unavailable | Not collected for this form/year |
-2 | Not applicable | Field doesn't apply to this entity |
-3 | Suppressed | Confidentiality restriction |
null | Not reported | Organization did not report (may have data) |
0 | Zero value | Explicitly reported as zero |
Important: In Portal data,
-1/-2/-3are integer values. However, empirically these codes are rare in the NCCS Portal dataset — most missing data appears asnullrather than negative codes. Only a handful of financial columns (e.g.,sale_sec_gross_net,changes_net_assets_other) contain any-1/-2/-3values. A0means the organization reported zero;nullmeans the organization did not report. These are distinct conditions.
Datasets for NCCS are available via the mirror system. See datasets-reference.md for canonical paths, mirrors.yaml for mirror configuration, and fetch-patterns.md for fetch code patterns.
| Dataset | Type | Years | Path | Codebook |
|---|---|---|---|---|
| 990 Forms | Single | 1993-2016 | nccs/colleges_nccs_all | nccs/codebook_colleges_nccs_form_990 |
Codebooks are .xls files co-located with data in all mirrors. Use get_codebook_url() from fetch-patterns.md to construct download URLs.
Truth Hierarchy: When interpreting variable values, apply this priority:
- Actual data file (what you observe in the parquet/CSV) — this IS the truth
- Live codebook (.xls in mirror) — authoritative documentation, may lag
- This skill documentation — convenient summary, may drift from codebook
If this documentation contradicts the codebook, trust the codebook. If the codebook contradicts observed data, trust the data and investigate.
The Portal dataset is pre-filtered to higher education institutions matched to IPEDS UNITIDs. NTEE codes are NOT included in the Portal data — for NTEE-based filtering, use the full NCCS BMF directly.
import polars as pl
# Filter by year
df_2015 = df.filter(pl.col("year") == 2015)
# Filter by state (integer FIPS codes)
df_ca = df.filter(pl.col("fips") == 6) # California
# Filter out null values from financial columns
df_valid = df.filter(
(pl.col("revenue_total").is_not_null()) &
(pl.col("revenue_total") >= 0) # Excludes rare -1/-2/-3 codes
)
# Replace negative codes with null for analysis (precautionary)
df = df.with_columns(
pl.when(pl.col("revenue_total") < 0)
.then(None)
.otherwise(pl.col("revenue_total"))
.alias("revenue_total_clean")
)
library(dplyr)
# Filter by year
df_2015 <- df |> filter(year == 2015)
# Filter by state (integer FIPS codes)
df_ca <- df |> filter(fips == 6) # California
# Filter out null values from financial columns
df_valid <- df |> filter(!is.na(revenue_total), revenue_total >= 0)
# Replace negative codes with NA for analysis (precautionary)
df <- df |> mutate(
revenue_total_clean = if_else(revenue_total < 0, NA_real_, revenue_total)
)
| Pitfall | Issue | Solution |
|---|---|---|
| Using string codes | Portal uses integer FIPS (6), not string ("CA" or "06") | Always use integer comparisons; filter >= 1 to exclude missing codes |
| Filing threshold confusion | Organizations under $200K revenue may file 990-EZ with fewer variables | Check form type; use Core PZ files for combined 990/990-EZ coverage |
| Fiscal year variation | Nonprofits have different fiscal year ends (June 30 common for colleges) | year = Portal academic year (fall semester); fiscal_year = IRS fiscal year end (typically year + 1). Filter on year for IPEDS joins. |
| No NTEE in Portal data | Portal dataset does not include NTEE codes; pre-filtered to higher ed institutions | Cannot filter by NTEE code; use full NCCS BMF for NTEE-based filtering |
| NTEE classification accuracy | ~25% of NTEE codes estimated to be imprecise | Use NCCS-corrected codes (NTEE_NCCS) over IRS-assigned codes when available |
| Consolidated filings | Some university systems file consolidated 990s covering multiple campuses | Check mult_ein_flag; one EIN may represent multiple institutions |
| Form version changes | Form 990 was redesigned in 2008; variable definitions changed | Be cautious comparing pre-2008 and post-2008 data for governance variables |
| Missing vs. zero | 0 means explicitly reported zero; null means not reported | Distinguish between zero-value and not-reported before aggregating |
| Aspect | NCCS (Form 990) | IPEDS |
|---|---|---|
| Coverage | All 501(c)(3) nonprofits | Title IV institutions only |
| Reporting Basis | IRS fiscal year | IPEDS survey cycles |
| Financial Framework | Nonprofit accounting (GAAP) | Education-specific categories |
| Governance | Detailed board/compensation data | Limited HR data |
| Programs | Mission statements, activities | Degree programs, enrollment |
| Identifier | EIN | UNITID |
| Update Frequency | Annual (with lag) | Annual |
Fetch data via fetch_from_mirrors("nccs/colleges_nccs_all")
unitid for IPEDS joiningFilter and clean
Link to IPEDS using unitid and year columns
Analyze — See variable definitions for meaning and limitations
Open the official catalog
https://urbaninstitute.github.io/nccs/catalogs/catalog-core.htmlChoose the product deliberately
Record release status before downloading
Identify and validate organizations
unitid; build or validate an EIN-UNITID crosswalk separatelyExtract, clean, and analyze
| Source | Relationship | When to Use |
|---|---|---|
education-data-source-ipeds | Complementary institution data | Join on EIN-UNITID crosswalk for enrollment, degrees, and education-specific financials |
education-data-explorer | Parent discovery skill | Routing questions to mirror dataset files |
education-data-query | Data fetching | Downloading parquet/CSV files |
| Topic | Reference File |
|---|---|
| BMF overview | ./references/nonprofit-data.md |
| Core data series | ./references/nonprofit-data.md |
| Efile database | ./references/nonprofit-data.md |
| Form 990 structure | ./references/form-990.md |
| Revenue variables | ./references/form-990.md |
| Expense variables | ./references/form-990.md |
| Balance sheet | ./references/form-990.md |
| Governance data | ./references/form-990.md |
| Schedule details | ./references/form-990.md |
| Linking to IPEDS | ./references/education-relevance.md |
| Private college identification | ./references/education-relevance.md |
| Supplementing education research | ./references/education-relevance.md |
| NTEE code structure | ./references/ntee-codes.md |
| Education NTEE codes | ./references/ntee-codes.md |
| NTEEV2 format | ./references/ntee-codes.md |
| Financial variables | ./references/variable-definitions.md |
| Variable naming conventions | ./references/variable-definitions.md |
| Data quality issues | ./references/variable-definitions.md |
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Guide for creating DAAF agent definition files. Covers 12-section template, hook registration, skills-in-frontmatter, integration checklist. Use when adding or revising agents. For SKILL.md files, use skill-authoring instead.
中文简介正在准备中。当前显示原文说明。
Researcher-facing analytic triangulation ("creative verification") for stress-testing provisional findings and designing pre-specified challenges before an analysis runs. Turns a researcher's concern or focal claim into competing explanations, bounded discriminating tests, audited diagnostic artifacts, and evidence-calibrated interpretations in a hypothesis/evidence ledger — behavioral, output-level verification replacing line-by-line code review. Covers 12 challenge families organized by Shadish-Cook-Campbell validity type, named sensitivity statistics, pre-committed interpretation rules, anti-fishing guardrails, and interactive diagnostic-artifact QA. Use in Ad Hoc Collaboration to verify, challenge, or stress-test a result, or to design discriminating tests before an analysis runs. Not code-change verification (verify skill / code review) and not final adjudication or re-execution (data-verifier, Reproducibility Verification) — prospective, hypothesis-driven challenge design of analytic claims.
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In-situ smoke testing that verifies a LIVE DAAF deployment functions end-to-end in whatever provider route it is configured for. Auto-detects the active install route (anthropic-subscription, openrouter, chatgpt-subscription shim, openai-api shim) and runs tiered probes: Tier 0 free preflight (route/env coherence, hooks, statuslines, shim health); Tier 1 one live round-trip (~cents); Tier 2 a six-probe functional battery (dispatch, coding, web, skill loading, isolation-strip, nested-dispatch deny); Tier D a zero-cost deterministic battery (bats, Pester, lint, safety-hook tests). Use after install, after a rebuild or update, after any provider/config change (new API key, model remap, shim change), for pre-release validation, or when asked "is my install working" or to "smoke test the deployment/config." Requires the DAAF_DEV=1 dev image; a contributor tool, not end-user-facing. NOT DAAFBench (model behavioral-adherence evaluation under benchmarks/) and NOT scripts/smoke_tests/ (R/Python library-package smoke tests).
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Operational framework for the DAAF orchestrator. Defines engagement modes, confirmation protocol, subagent dispatch, context budget, and reference-loading. Loaded exclusively by the orchestrator — not for subagents or user questions.
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Data science methodology and method-selection routing for quantitative research. Covers EDA, data validation, descriptive analysis, causal inference (IV, DiD, RD, synthetic control), clustering/PCA/UMAP, supervised ML, geospatial analysis, network analysis, and visualization design. Contains the canonical method-to-library routing tree, routed by execution language — Python: statsmodels (OLS/GLM/time series), pyfixest (FE/DiD), linearmodels (RE/GMM/SUR), svy (complex surveys), scikit-learn (clustering/prediction ML), geopandas (spatial), igraph (network analysis); R: r-stats (OLS/GLM/time series), fixest (FE/DiD), plm (panel/RE/IV), survey-r (complex surveys), tidymodels (ML), sf-terra (spatial), igraph-r (network analysis). Load the routed tool-specific skill before giving tool-specific advice or writing code — library skills encode environment constraints and curated caveats absent from general knowledge.
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Interpretation guidance for Urban Institute Education Data Portal datasets. The Portal is a curation layer over federal data: lowercase variable names, integer-encoded categoricals, standardized missing codes (-1 missing, -2 not applicable, -3 suppressed). Covers year definitions, grade encoding (grade=-1 is Pre-K, not missing), suppression rates, ODC-By licensing, and cross-source join identifiers. Load before analyzing any Portal data. Routes to source-specific deep-dive skills for individual datasets.
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