scope-guard-before-execution
Skill0 starsChanged 14 days agoMITView on GitHub
Check the engagement scope before a tool touches a target, and refuse rather than warn. Use when a tool can act on arbitrary hosts and the agent may have the wrong target in context
In this repository49 other files it gives its agents.
- argument-construction-from-artifactsSkill
- audit-log-of-tool-callsSkill
- bounded-output-designSkill
- capability-negotiation-checkSkill
- changelog-and-versioningSkill
- concurrency-and-ordering-checkSkill
- context-window-managementSkill
- credential-isolationSkill
- data-retention-policySkill
- description-as-contractSkill
- destructive-action-confirmationSkill
- destructive-tool-gatingSkill
- deterministic-command-choicesSkill
- done-when-criteriaSkill
- error-shape-for-agentsSkill
- fixture-driven-transcript-testsSkill
- human-in-the-loop-escalationSkill
- idempotency-annotationSkill
- input-schema-strictnessSkill
- least-privilege-tool-grantsSkill
- lifecycle-test-initialize-then-toolsSkill
- local-vs-remote-boundarySkill
- one-procedure-per-skillSkill
- pagination-and-limit-disciplineSkill
- parallel-tool-call-safetySkill
- protocol-conformance-testSkill
- protocol-version-handshakeSkill
- publishing-a-pack-locallySkill
- rate-limit-respectSkill
- reference-canonicalisationSkill
- replay-transcript-for-regressionSkill
- restart-and-reload-semanticsSkill
- search-then-fetch-patternSkill
- secrets-via-environmentSkill
- server-discovery-and-trustSkill
- signal-and-pitfall-sectionsSkill
- skill-frontmatter-contractSkill
- stdio-client-configSkill
- stdout-purity-checkSkill
- third-party-server-sandboxingSkill
- tool-call-budgetingSkill
- tool-call-error-pathsSkill
- tool-error-without-retry-stormSkill
- tools-list-schema-validationSkill
- tool-surface-minimisationSkill
- tool-verb-namingSkill
- transport-choiceSkill
- verify-tool-output-before-reportingSkill
- when-to-use-and-avoidSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 25
Test a target one character outside the list and confirm refusal
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Scope Guard Before Execution
Check the engagement scope before a tool touches a target, and refuse rather than warn
Use when: a tool can act on arbitrary hosts and the agent may have the wrong target in context
Avoid when: the tool is a pure reader of local packs with no target concept
Procedure
- Load the in-scope asset list at startup, failing when it is absent
- Normalise each requested target before comparison
- Refuse any target that does not match the list exactly
- Return a refusal that names the target and the reason
- Log refusals so repeated mistakes are visible
- Test a target one character outside the list and confirm refusal
Signals
- an out-of-scope target is refused, not merely warned about
- the refusal message quotes the requested and the allowed assets
- refusals are logged with a timestamp
- a near-miss target such as a lookalike domain is refused
Patterns
1. Exact match
target in scope_set, with normalised case and trailing dot2. Refusal shape
refused: evil.example is not in scope3. Near-miss test
api.example.test.evil.example refusedPitfalls
- Warning about scope and continuing, which is the same as no guard
- Matching on a substring so a lookalike domain passes
- Caching the scope list so a mid-engagement change is ignored
Done when
- an out-of-scope target produces a refusal and no action
- a lookalike domain is proven to be refused
References
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

