io.github.beepboop2025/palimpsest
repo:https://github.com/beepboop2025/palimpsest
Rights-aware censorship, China-economic status, and tamper-evident AI evaluation tools.
- transport:
- remote
- credential class:
- self-provisionable
Owner verification
Not yet verified. Verifying proves you control this server and is free, permanently — it never changes a published score.
Start verification →Tools
- get_newsroomshallow
Read one evidence-first reporting surface without scraping a page or guessing a filename. Views: 'newsroom' for prioritized deterministic stories, 'wire' for normalized source dossiers, 'economy' for the currently restricted China economic pulse, 'machine-analysis' for the currently restricted AnalysisReports and AbstentionReports, 'investigations' for review-gated research leads, 'editorial-readiness' for publication gates, and 'interconnection' for named-key fat-object joins on China situation events (topic-surface-only, never wire corroboration). The economy, machine-analysis and interconnection views are metadata-only until a lineage-filtered rebuild removes denied derivatives. Availability never implies publication readiness: statuses, gates, counterevidence, limitations and right-to-reply state stay attached.
- get_signalshallow
Read one named signal. Permitted signals return their bounded latest payload; China-economic signals in the denied lineage closure return explicit restricted/unavailable rights metadata and no values. Call list_signals first to discover valid names. Use this for the AI-model-evaluation side too: 'eval-registry' returns the pre-registered, hash-chained eval ledger with its verified flag and Merkle root, 'gfi-transcripts' returns a bounded view of the complete GFI v2 response matrix, and 'refusal-drift' returns the current frontier-model refusal reading on the frozen benign probe set; read 'eval-assurance' before turning either into a validity claim, and 'eval-journal' for the evidence-bound explanation and source receipts, or 'eval-findings' for the current deterministic article edition. Distinct from gfw_reading, which merges the two Great Firewall layers into one combined view.
- gfw_readingshallow
Read the Great Firewall's current state at both layers in one call: live network blocking measured inside China via OONI (website, messenger and circumvention-tool reachability) joined with model-layer censorship from the Generative Firewall Index over Chinese LLMs. Takes no arguments. A combined convenience view — for one layer's full raw payload use get_signal with 'ooni-gfw' or 'generative-firewall-index'.
- list_signalsshallow
List every published signal Palimpsest exposes across its three applications: name, one-line description and source URL for each. Censorship and information control — OONI Great Firewall probes, Censored Planet, IODA outages, circumvention demand, takedown and redaction pressure, and the board's own verdict. China economics — explicit metadata-only rights status for affected observations, pulse, forecast and derivative surfaces; no denied values are returned. AI model evaluation — the tamper-evident, pre-registered eval registry (hash-chained and Merkle-rooted), its claim-by-claim assurance ceiling, evidence-bound Eval Journal, deterministic live findings, and frontier-model refusal drift, alongside the Generative Firewall Index over a named China-focused panel. Takes no arguments. Call this first to discover signal names, then get_signal for one full reading.
- query_economic_observationsshallow
Inspect the native publication-rights status for the China-economic observation surface. The reviewed default-deny policy does not authorize redistribution of current CFETS/ChinaMoney values, so this tool returns policy digest, UTC clocks, per-source decisions and zero published-record status only. It never reads or returns observation rows, empty row arrays, derived signals, or neutral replacements. Filters are validated for contract compatibility but cannot override source rights.
- whats_happeningshallow
Judge whether anything is happening in Chinese censorship right now, across every signal at once: the board's own cross-signal verdict with the multiplicity paid for (false-discovery control) and coverage confounds flagged as measurement artifacts, never findings. Takes no arguments. Use this instead of fetching signals individually and reconciling them yourself; then use get_signal to drill into whichever signal moved. Scope note: this is the censorship board. For the AI-model-evaluation side use get_signal with 'eval-registry', 'eval-assurance' or 'refusal-drift'.
Embed this server’s score
Tool count and median score across every tool in this server’s corpus — honest in a way a single cherry-picked tool’s badge wouldn’t be.
[](https://vouch.tools/servers/b143302b-1d82-499f-8e87-ddc968b9348f)