Low Risk

get_compensation_signatures

Query the compensation-signatures lens: how stereotyped is your chain-shape behavior, and which chain patterns dominate vs which are exploratory? Every multi-step chain the agent runs is fingerprinted as an ordered target sequence (e.g. api:openai.com → api:stripe.com → mcp:filesystem). Across a...

Bulk/mass operation — affects multiple targets

Part of the ACR — Agent Composition Records MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

@tethral/acr-mcp Read Risk 2/5

AI agents call get_compensation_signatures to retrieve information from ACR — Agent Composition Records without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though get_compensation_signatures only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

acr-agent-composition-records.yaml
tools:
  get_compensation_signatures:
    rules:
      - action: allow

See the full ACR — Agent Composition Records policy for all 25 tools.

Tool Name get_compensation_signatures
Category Read
Risk Level Low

View all 25 tools →

Agents calling read-class tools like get_compensation_signatures have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.

What does the get_compensation_signatures tool do? +

Query the compensation-signatures lens: how stereotyped is your chain-shape behavior, and which chain patterns dominate vs which are exploratory? Every multi-step chain the agent runs is fingerprinted as an ordered target sequence (e.g. api:openai.com → api:stripe.com → mcp:filesystem). Across a window, the lens reports: • agent_stability — a continuum score in [0, 1]. 1.0 = one pattern does everything (maximally routine). 0.0 = every chain looks different (exploratory / unstable). Computed as 1 − normalized Shannon entropy across patterns. • pattern_stability — per-pattern share of total chains. A high value means this exact sequence is the agent's routine. A low value with persistent frequency is the kind of long-tail signal that *can* be compensation (routing around something) or genuinely exploratory — you read it together with the friction report. • fleet_agent_count — how many other agents run this same pattern. A high-frequency, low-fleet pattern is idiosyncratic. A fleet-wide pattern is a substrate-level signal. This is a continuum, not a verdict. There is no "compensation detected" flag — only the distribution. Interpret a persistent low-stability tail with non-trivial frequency as *possible* ongoing compensation, and confirm by cross-referencing the friction report for the targets involved. Requires at least some multi-step chains to have been logged with chain_id + chain_position. Window is 'day' or 'week'; defaults to 'week'. Runs against chain_analysis, which is refreshed nightly by the background job.. It is categorised as a Read tool in the ACR — Agent Composition Records MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_compensation_signatures? +

Add a rule in your Intercept YAML policy under the tools section for get_compensation_signatures. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the ACR — Agent Composition Records MCP server.

What risk level is get_compensation_signatures? +

get_compensation_signatures is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_compensation_signatures? +

Yes. Add a rate_limit block to the get_compensation_signatures rule in your Intercept policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block get_compensation_signatures completely? +

Set action: deny in the Intercept policy for get_compensation_signatures. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides get_compensation_signatures? +

get_compensation_signatures is provided by the ACR — Agent Composition Records MCP server (@tethral/acr-mcp). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policies on ACR — Agent Composition Records

Open source. One binary. Zero dependencies.

npx -y @policylayer/intercept
github.com/policylayer/intercept →
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