Three pattern checks (F01, F02, F03) run uniformly against every $1M+ federal prime contract in the dataset. The fourth card below describes the structural filter that strips false positives before flags publish. Together they are the entire screening framework. A fired flag is descriptive, not a finding: many flagged awards have routine explanations and are best read as worth a closer look.
What it checks. The award obligation exceeds ten million dollars, the recipient has no federal awards predating this one in the dataset, and the award was non-competitive.
Why it matters. A vendor with no prior federal history receiving a large non-competitive award is statistically uncommon. Both conditions independently warrant scrutiny; their co-occurrence at this dollar level is rare and worth a closer look.
What it checks. The award obligation exceeds twenty-five million dollars, the recipient has no federal awards predating this one in the dataset, and the award was issued as a competitive solicitation that received only one offer.
Why it matters. A competitive solicitation that draws a single offer from a vendor with no prior federal history is statistically uncommon at this dollar threshold. Distinct from F01: F01 catches awards where competition was waived; this flag catches awards where competition was nominal but produced no contest.
What it checks. The award obligation exceeds twenty-five million dollars, and the recipient has no federal awards predating this one in the dataset. Unlike F01 and F02, F03 does not consider how the contract is classified for competition. It fires regardless of whether the award is recorded as sole-source or competitive.
Why it matters. F03 catches awards that public reporting describes as effectively no-bid even when the formal procurement record classifies them differently. F01 catches awards explicitly recorded as sole-source; F02 catches competitive solicitations that drew only one offer. F03 closes the gap by treating the dollar size itself as the signal: a first contract above twenty-five million dollars to an entity with no federal history is statistically uncommon regardless of how the procurement was coded.
What it does. The structural filter is a second pass that removes flag matches with a known, non-anomalous explanation. What publishes is the subset that does not have one.
Why it matters. The flags rely on "no prior federal contracts" as a meaningful signal. That signal breaks when the entity is legally new but operationally familiar. A subsidiary spun up for one contract carries the parent's federal history under a different UEI. A joint venture formed for a single procurement is brand-new by definition. A facility operator with a fresh legal name continues work that has been federally funded for years. The filter removes these so the published set reflects entities actually new to federal business.
A flag is descriptive, not a finding. It means an award matches a statistical pattern that is uncommon at the dollar threshold for that flag. Many flagged awards have routine explanations. The flagging is a starting point for inquiry, not a conclusion.
Every flagged row links to its USASpending record so the underlying contract can be reviewed directly.
The three flags all target the same underlying pattern: a recipient with no prior federal contract history pulling a large award. They differ in which procurement pathway carried the award through.
F01 catches the explicit version (sole-source above $10M). F02 catches the soft version (competitive solicitation that drew exactly one offer above $25M). F03 catches the implicit version (a first-ever federal contract above $25M regardless of competition mechanism). One pattern, three doors.
This pattern category is timeless: whatever the FAR looks like after the current rewrite, a brand-new entity pulling a huge contract will remain worth watching, because the procurement record will still capture vendor history and award size regardless of how the surrounding regulation gets reshaped.
The data source is USASpending.gov, the federal government's authoritative public spending dataset. Specifically, the annual "All Contracts Full" bulk archive ZIPs at files.usaspending.gov/award_data_archive/, which contain the transaction-level history for each fiscal year.
Every flagged award on the dashboard links back to its USASpending record so the underlying contract can be reviewed directly.
The dashboard refreshes monthly from the latest USASpending bulk archive snapshot. USASpending publishes the monthly snapshot on the 5th or 6th of each month; the refresh fires on the 8th to give the upstream data a buffer to settle. The dashboard's freshness window is therefore up to 30 days.
The monthly cadence is deliberate. The flag patterns target multi-year shell-like structures rather than time-sensitive activity, and a monthly bulk-archive snapshot is a more stable, reproducible source than ad-hoc API polling.
Without it, the dashboard would be flooded with awards that fire the no-prior-history pattern by program design rather than by anomaly. A federal-prime subsidiary spinning up under a new legal entity, an Alaska Native Corporation subsidiary, a joint venture formed for one specific procurement, a Federally Funded Research and Development Center operator transition, a healthcare provider getting its first Medicare contract, a foreign government recipient, or a bridge contract extension under a new vehicle: every one of these will trigger F01, F02, or F03 by structure, not by anomaly.
The structural filter strips these mechanically explainable cases before publication so the dashboard surfaces only the residual signal: awards where the no-prior-history pattern is not explained by entity type, sector, or contract architecture. Approximately 1,400 individually verified recipient names are baked into the filter alongside the structural rules.
They match a structural filter rule (municipal authority, hospital, joint venture, federal-prime subsidiary, Alaska Native Corporation or tribal entity, foreign government recipient, bridge contract extension, FFRDC operator, etc.) where the absence of prior federal history is explained by the entity type or contract structure rather than by anomaly. The structural filter strips these before the flag reaches the dashboard.
The filter has two layers: pattern-based structural rules (federal-prime subsidiaries, ANCs, joint ventures, FFRDC operators, healthcare providers, foreign government recipients, bridge contracts, etc.) and a curated list of individually verified recipient names. Pattern rules catch entities by structural signal; the curated list handles cases where the structural signal is ambiguous and individual verification is needed.
For the curated list, candidates are batched and verified against SAM.gov entity records (formation date, address, business types, ownership, registration history), USASpending contract history (prior federal work under the same UEI), and public web sources (company website, news coverage, public-company filings). Verification looks for clear indicators of an established legitimate entity: real physical address, formation well before the federal contract, real product or service, business activity consistent with the contract type, recognizable corporate identity. Entities that pass on all dimensions are added to the curated list.
The batched investigation is performed by Claude Opus models running against the data sources above, with each batch reviewed and approved by a human before names are committed to the structural filter. When verification is ambiguous, the entity stays on the dashboard for human review rather than getting safelisted. Better to leave a legitimate company flagged than to safelist a wholesome-named shell. The filter is updated periodically rather than on every monthly refresh; the current curated list reflects investigation of recipients flagged across FY18-FY26 contract data.
Yes. The "Export CSV" button in the page header generates a CSV of the currently visible awards, respecting any active filters and sort order, and triggers a browser download. The file contains 18 columns including PIID, recipient, UEI, agency, obligation, action date, contract type, competition mechanism, flag codes, flag rationale, and the USASpending record link.
The CSV is generated client-side from the loaded JSON. No server round-trip and no separate export step.
Empirical testing settled this. The relationship between load floor and useful flag output is U-shaped, and $1M sits at the bottom of the curve.
Below $1M: tiny follow-on contracts begin counting as "prior federal history" to the algorithm. Shell-pattern awards where a brand-new entity receives a large first contract and then a small administrative follow-on shortly after get masked: the small follow-on looks like prior experience, so the large first award no longer flags. The entities most worth attention drop off the list.
At $1M: shells stand out, and mid-size vendors with genuine $1M-and-above prior history are properly excluded. The dashboard surfaces the entities that have no real federal track record before pulling a large award.
Above $1M: legitimate mid-size vendors whose biggest prior contract was in the $1M to $5M range start qualifying as "no history" because their real history is no longer visible. The list fills with established companies whose federal footprint just happens to sit below the higher floor. More volume, lower signal-to-noise ratio.
The three flag thresholds themselves ($10M for F01 sole-source, $25M for F02 and F03) sit well above the load floor. Awards between $1M and the flag threshold contribute to the prior-history lookback but never trigger a flag themselves.
The flag thresholds compare against current_total_value_of_award, which represents the contract ceiling: the government's committed total value, including all option years and ceiling raises to date. This is more useful for shell-pattern detection than per-transaction obligation, because the ceiling reflects the trust signal being extended to the vendor.
October 2014 is the start of federal fiscal year 2015. The federal fiscal year runs October 1 through September 30, named for the calendar year in which it ends. FY15 = Oct 1, 2014 through Sep 30, 2015. The loader pulls FY15 onward into the database so the no-prior-history check has a real lookback window for FY18 candidates. Flagged awards on the dashboard begin at FY18; FY15-17 records are loaded as history context only and are never themselves evaluated as flag candidates.
Independent and open source. No affiliation with any federal agency, contractor, or funding source. github.com/contractwatch, MIT licensed.